\n

\n \n 2024\n \n \n (6)\n \n \n

\n

\n \n \n

\n \n\n \n \n \n \n \n \n How much data do we need to estimate computational models of decision-making? The COMPASS toolbox.\n \n \n \n \n\n\n \n Beeckmans, Maud; Huycke, P.; Verguts, T.; and Verbeke, P.\n\n\n \n\n\n\n BEHAVIOR RESEARCH METHODS. 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"How$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{01H6B0N2MJYPGXV9D7GJ68PKV4,\n  abstract     = {{How much data are needed to obtain useful parameter estimations from a computational model? The standard approach to address this question is to carry out a goodness-of-recovery study. Here, the correlation between individual-participant true and estimated parameter values determines when a sample size is large enough. However, depending on one's research question, this approach may be suboptimal, potentially leading to sample sizes that are either too small (underpowered) or too large (overcostly or unfeasible). In this paper, we formulate a generalized concept of statistical power and use this to propose a novel approach toward determining how much data is needed to obtain useful parameter estimates from a computational model. We describe a Python-based toolbox (COMPASS) that allows one to determine how many participants are needed to fit one specific computational model, namely the Rescorla-Wagner model of learning and decision-making. Simulations revealed that a high number of trials per person (more than the number of persons) are a prerequisite for high-powered studies in this particular setting.}},\n  author       = {{Beeckmans, Maud and Huycke, Pieter and Verguts, Tom and Verbeke, Pieter}},\n  issn         = {{1554-351X}},\n  journal      = {{BEHAVIOR RESEARCH METHODS}},\n  keywords     = {{Computational models,Statistical power,Toolbox}},\n  language     = {{eng}},\n  title        = {{How much data do we need to estimate computational models of decision-making? The COMPASS toolbox}},\n  url          = {{http://doi.org/10.3758/s13428-023-02165-7}},\n  year         = {{2024}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n Humans adaptively select different computational strategies in different learning environments.\n \n \n \n\n\n \n Verbeke, Pieter; and Verguts, T.\n\n\n \n\n\n\n PSYCHOLOGICAL REVIEW. 2024.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{01HNA7HEGNWPEHY32FJ2G5MMCK,\n  author       = {{Verbeke, Pieter and Verguts, Tom}},\n  issn         = {{0033-295X}},\n  journal      = {{PSYCHOLOGICAL REVIEW}},\n  language     = {{eng}},\n  title        = {{Humans adaptively select different computational strategies in different learning environments}},\n  year         = {{2024}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n Reinforcement learning and meta-decision making.\n \n \n \n\n\n \n Verbeke, Pieter; and Verguts, T.\n\n\n \n\n\n\n CURRENT OPINION IN BEHAVIORAL SCIENCES. 2024.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{01HQ7VEBHM96KX3FE8GBECHJRT,\n  author       = {{Verbeke, Pieter and Verguts, Tom}},\n  issn         = {{2352-1546}},\n  journal      = {{CURRENT OPINION IN BEHAVIORAL SCIENCES}},\n  language     = {{eng}},\n  title        = {{Reinforcement learning and meta-decision making}},\n  year         = {{2024}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Learning where to be flexible : using environmental cues to regulate cognitive control.\n \n \n \n \n\n\n \n Xu, Shengjie; Simoens, J.; Verguts, T.; and Braem, S.\n\n\n \n\n\n\n JOURNAL OF EXPERIMENTAL PSYCHOLOGY-GENERAL, 153(2): 328–338. 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Learning$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{01HEJGGCXKNH7FHK8VER0ED9R1,\n  abstract     = {{Cognitive flexibility refers to a mental state that allows efficient switching between tasks. While deciding to be flexible is often ascribed to a strategic resource-intensive executive process, people may also simply use their environment to trigger different states of cognitive flexibility. We developed a paradigm where participants were exposed to two environments with different task-switching probabilities, followed by a probe phase to test the impact of environmental cues. Our results show that people were more efficient at switching in a high-switch environment. Critically, we observe environment-specific triggering of cognitive flexibility after a 4-day training period (Experiment 2, N = 51), but not after a 1-day training period (Experiment 1, N = 52). Together, these findings suggest that people can associate the need for cognitive flexibility with their environment, providing an environmental triggering mechanism for cognitive control.}},\n  author       = {{Xu, Shengjie and Simoens, Jonas and Verguts, Tom and Braem, Senne}},\n  issn         = {{0096-3445}},\n  journal      = {{JOURNAL OF EXPERIMENTAL PSYCHOLOGY-GENERAL}},\n  keywords     = {{Developmental Neuroscience,General Psychology,Experimental and Cognitive Psychology,cognitive flexibility,cognitive control,context,task-switching,associative learning,HIERARCHICAL CONTROL,MEMORY,SLEEP,MODULATION,STABILITY,SELECTION,CORTEX,REWARD}},\n  language     = {{eng}},\n  number       = {{2}},\n  pages        = {{328--338}},\n  title        = {{Learning where to be flexible : using environmental cues to regulate cognitive control}},\n  url          = {{http://doi.org/10.1037/xge0001488}},\n  volume       = {{153}},\n  year         = {{2024}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Manipulating prior beliefs causally induces under- and overconfidence.\n \n \n \n \n\n\n \n Van Marcke, Hélène; Le Denmat, P.; Verguts, T.; and Desender, K.\n\n\n \n\n\n\n PSYCHOLOGICAL SCIENCE. 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Manipulating$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{01HNAB73SQ79KZJDG3W2NTJW44,\n  abstract     = {{Making a decision is invariably accompanied by a sense of confidence in that decision. Across subjects and tasks, there is widespread variability in the exact level of confidence, even for tasks that do not differ in objective difficulty. Such expressions of under- and overconfidence are of vital importance, as they relate to fundamental life outcomes. Yet, a computational account specifying the mechanisms underlying underand overconfidence is currently missing. Here, we propose that prior beliefs in the ability to perform a task, based on prior experience with this or a similar task, explain why confidence can differ dramatically across subjects and tasks, despite similar performance. In two perceptual decision-making experiments, we provide evidence for this hypothesis by showing that manipulating prior beliefs about task performance in a training phase causally influences reported levels of confidence in a test phase, while leaving objective performance in the test phase unaffected. This is true both when prior beliefs are induced via manipulated comparative feedback and via manipulating task difficulty during the training phase. We account for these results within an accumulation-to-bound model by explicitly modeling prior beliefs based on earlier exposure to the task. Decision confidence is then quantified as the probability of being correct conditional on these prior beliefs, leading to under- or overconfidence depending on the task context. Our results provide a fundamental mechanistic insight into the computations underlying under- and overconfidence in perceptual decision-making.}},\n  author       = {{Van Marcke, Hélène and Le Denmat, Pierre and Verguts, Tom and Desender, Kobe}},\n  issn         = {{0956-7976}},\n  journal      = {{PSYCHOLOGICAL SCIENCE}},\n  keywords     = {{open data,drift-diffusion model,under- and overconfidence,priors,decision-making,metacognition}},\n  language     = {{eng}},\n  title        = {{Manipulating prior beliefs causally induces under- and overconfidence}},\n  url          = {{http://doi.org/10.1177/09567976241231572}},\n  year         = {{2024}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Learning environment-specific learning rates.\n \n \n \n \n\n\n \n Simoens, Jonas; Verguts, T.; and Braem, S.\n\n\n \n\n\n\n PLOS COMPUTATIONAL BIOLOGY, 20(3): 23. 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Learning$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{01HRYTS646J0SGC03MC64RZHGG,\n  abstract     = {{People often have to switch back and forth between different environments that come with different problems and volatilities. While volatile environments require fast learning (i.e., high learning rates), stable environments call for lower learning rates. Previous studies have shown that people adapt their learning rates, but it remains unclear whether they can also learn about environment-specific learning rates, and instantaneously retrieve them when revisiting environments. Here, using optimality simulations and hierarchical Bayesian analyses across three experiments, we show that people can learn to use different learning rates when switching back and forth between two different environments. We even observe a signature of these environment-specific learning rates when the volatility of both environments is suddenly the same. We conclude that humans can flexibly adapt and learn to associate different learning rates to different environments, offering important insights for developing theories of meta-learning and context-specific control.\n\nPeople constantly have to make decisions, such as what to wear for the day, or which pizza to order at a restaurant. Fortunately, people can learn from past decisions to inform future ones. However, environments may be unstable: The best pizza today is not necessarily the best pizza tomorrow. The chef may have had a bad day, in which case no learning needs to take place, or the restaurant may have changed chefs, in which case learning needs to restart from scratch. For this reason, it pays off to learn the instabilities of different environments: Which pizza is best may change more often in one restaurant than in another (e.g., because chefs change more quickly in one restaurant than in another). Formally, environmental instability determines how strongly one should update the expected value of an option (e.g., a pizza) based on novel information, often referred to as the learning rate. We thus investigated if people can learn different learning rates for different environments. We demonstrated that they can: Participants randomly and quickly alternated between a stable and an unstable environment, and they learned to use higher learning rates in the unstable than in the stable environment.}},\n  articleno    = {{e1011978}},\n  author       = {{Simoens, Jonas and Verguts, Tom and Braem, Senne}},\n  issn         = {{1553-734X}},\n  journal      = {{PLOS COMPUTATIONAL BIOLOGY}},\n  language     = {{eng}},\n  number       = {{3}},\n  pages        = {{23}},\n  title        = {{Learning environment-specific learning rates}},\n  url          = {{http://doi.org/10.1371/journal.pcbi.1011978}},\n  volume       = {{20}},\n  year         = {{2024}},\n}\n\n

\n

\n\n\n

\n People often have to switch back and forth between different environments that come with different problems and volatilities. While volatile environments require fast learning (i.e., high learning rates), stable environments call for lower learning rates. Previous studies have shown that people adapt their learning rates, but it remains unclear whether they can also learn about environment-specific learning rates, and instantaneously retrieve them when revisiting environments. Here, using optimality simulations and hierarchical Bayesian analyses across three experiments, we show that people can learn to use different learning rates when switching back and forth between two different environments. We even observe a signature of these environment-specific learning rates when the volatility of both environments is suddenly the same. We conclude that humans can flexibly adapt and learn to associate different learning rates to different environments, offering important insights for developing theories of meta-learning and context-specific control. People constantly have to make decisions, such as what to wear for the day, or which pizza to order at a restaurant. Fortunately, people can learn from past decisions to inform future ones. However, environments may be unstable: The best pizza today is not necessarily the best pizza tomorrow. The chef may have had a bad day, in which case no learning needs to take place, or the restaurant may have changed chefs, in which case learning needs to restart from scratch. For this reason, it pays off to learn the instabilities of different environments: Which pizza is best may change more often in one restaurant than in another (e.g., because chefs change more quickly in one restaurant than in another). Formally, environmental instability determines how strongly one should update the expected value of an option (e.g., a pizza) based on novel information, often referred to as the learning rate. We thus investigated if people can learn different learning rates for different environments. We demonstrated that they can: Participants randomly and quickly alternated between a stable and an unstable environment, and they learned to use higher learning rates in the unstable than in the stable environment.\n

\n\n\n

\n\n\n\n\n\n

\n

\n \n 2023\n \n \n (2)\n \n \n

\n

\n \n \n

\n \n\n \n \n \n \n \n \n Modulating hierarchical learning by high-definition transcranial alternating current stimulation at theta frequency.\n \n \n \n \n\n\n \n Liu, Meng; Dong, W.; Wu, Y.; Verbeke, P.; Verguts, T.; and Chen, Q.\n\n\n \n\n\n\n CEREBRAL CORTEX, 33(8): 4421–4431. 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"Modulating$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8767780,\n  abstract     = {{Considerable evidence highlights the dorsolateral prefrontal cortex (DLPFC) as a key region for hierarchical (i.e. multilevel) learning. In a previous electroencephalography (EEG) study, we found that the low-level prediction errors were encoded by frontal theta oscillations (4-7 Hz), centered on right DLPFC (rDLPFC). However, the causal relationship between frontal theta oscillations and hierarchical learning remains poorly understood. To investigate this question, in the current study, participants received theta (6 Hz) and sham high-definition transcranial alternating current stimulation (HD-tACS) over the rDLPFC while performing the probabilistic reversal learning task. Behaviorally, theta tACS induced a significant reduction in accuracy for the stable environment, but not for the volatile environment, relative to the sham condition. Computationally, we implemented a combination of a hierarchical Bayesian learning and a decision model. Theta tACS induced a significant increase in low-level (i.e. probability-level) learning rate and uncertainty of low-level estimation relative to sham condition. Instead, the temperature parameter of the decision model, which represents (inverse) decision noise, was not significantly altered due to theta stimulation. These results indicate that theta frequency may modulate the (low-level) learning rate. Furthermore, environmental features (e.g. its stability) may determine whether learning is optimized as a result.}},\n  author       = {{Liu, Meng and Dong, Wenshan and Wu, Yiling and Verbeke, Pieter and Verguts, Tom and Chen, Qi}},\n  issn         = {{1047-3211}},\n  journal      = {{CEREBRAL CORTEX}},\n  keywords     = {{ANTERIOR CINGULATE,PREDICTION ERRORS,PREFRONTAL CORTEX,FRONTAL THETA,DOPAMINE,BEHAVIOR,MODEL,INFORMATION,EXPLORATION,PERFORMANCE,high-definition tACS,dorsolateral prefrontal cortex,hierarchical,learning,computational modeling}},\n  language     = {{eng}},\n  number       = {{8}},\n  pages        = {{4421--4431}},\n  title        = {{Modulating hierarchical learning by high-definition transcranial alternating current stimulation at theta frequency}},\n  url          = {{http://doi.org/10.1093/cercor/bhac352}},\n  volume       = {{33}},\n  year         = {{2023}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n The neural substrates of how model-based learning affects risk taking : functional coupling between right cerebellum and left caudate.\n \n \n \n \n\n\n \n Huo, Hangfeng; Lesage, E.; Dong, W.; Verguts, T.; Seger, C. A.; Diao, S.; Feng, T.; and Chen, Q.\n\n\n \n\n\n\n BRAIN AND COGNITION, 172: 12. 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"The$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{01HCY79ZVN5RC67D7WT1S1DZW1,\n  abstract     = {{Higher executive control capacity allows people to appropriately evaluate risk and avoid both excessive risk aversion and excessive risk-taking. The neural mechanisms underlying this relationship between executive function and risk taking are still unknown. We used voxel-based morphometry (VBM) analysis combined with resting-state functional connectivity (rs-FC) to evaluate how one component of executive function, model-based learning, relates to risk taking. We measured individuals' use of the model-based learning system with the twostep task, and risk taking with the Balloon Analogue Risk Task. Behavioral results indicated that risk taking was positively correlated with the model-based weighting parameter omega. The VBM results showed a positive association between model-based learning and gray matter volume in the right cerebellum (RCere) and left inferior parietal lobule (LIPL). Functional connectivity results suggested that the coupling between RCere and the left caudate (LCAU) was correlated with both model-based learning and risk taking. Mediation analysis indicated that RCere-LCAU functional connectivity completely mediated the effect of model-based learning on risk taking. These results indicate that learners who favor model-based strategies also engage in more appropriate risky behaviors through interactions between reward-based learning, error-based learning and executive control subserved by a caudate, cerebellar and parietal network.}},\n  articleno    = {{106088}},\n  author       = {{Huo, Hangfeng and Lesage, Elise and Dong, Wenshan and Verguts, Tom and Seger, Carol A. and Diao, Sitong and Feng, Tingyong and Chen, Qi}},\n  issn         = {{0278-2626}},\n  journal      = {{BRAIN AND COGNITION}},\n  keywords     = {{Cognitive Neuroscience,Arts and Humanities (miscellaneous),Developmental and Educational Psychology,Experimental and Cognitive Psychology,Neuropsychology and Physiological Psychology,Decision making,Risk taking,Model-based learning,Functional,connectivity,Resting-state fMRI,DECISION-MAKING,PREFRONTAL CORTEX,INTERNAL-MODELS,BASAL GANGLIA,HUMAN BRAIN,CONNECTIVITY,NETWORKS,TASK,MECHANISMS,DISTINCT}},\n  language     = {{eng}},\n  pages        = {{12}},\n  title        = {{The neural substrates of how model-based learning affects risk taking : functional coupling between right cerebellum and left caudate}},\n  url          = {{http://doi.org/10.1016/j.bandc.2023.106088}},\n  volume       = {{172}},\n  year         = {{2023}},\n}\n\n

\n

\n\n\n\n\n\n

\n

\n \n 2022\n \n \n (11)\n \n \n

\n

\n \n \n

\n \n\n \n \n \n \n \n \n Neural representations of task context and temporal order during action sequence execution.\n \n \n \n \n\n\n \n Shahnazian, Danesh; Senoussi, M.; Krebs, R.; Verguts, T.; and Holroyd, C.\n\n\n \n\n\n\n TOPICS IN COGNITIVE SCIENCE, 14(2): 223–240. 2022.\n \n\n\n\n
\n\n\n\n \n \n $\"Neural$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8719047,\n  abstract     = {{Routine action sequences can share a great deal of similarity in terms of their stimulus response mappings. As a consequence, their correct execution relies crucially on the ability to preserve contextual and temporal information. However, there are few empirical studies on the neural mechanism and the brain areas maintaining such information. To address this gap in the literature, we recently recorded the blood-oxygen level dependent (BOLD) response in a newly developed coffee-tea making task. The task involves the execution of four action sequences that each comprise six consecutive decision states, which allows for examining the maintenance of contextual and temporal information. Here, we report a reanalysis of this dataset using a data-driven approach, namely multivariate pattern analysis, that examines context-dependent neural activity across several predefined regions of interest. Results highlight involvement of the inferior-temporal gyrus and lateral prefrontal cortex in maintaining temporal and contextual information for the execution of hierarchically organized action sequences. Furthermore, temporal information seems to be more strongly encoded in areas over the left hemisphere.}},\n  author       = {{Shahnazian, Danesh and Senoussi, Mehdi and Krebs, Ruth and Verguts, Tom and Holroyd, Clay}},\n  issn         = {{1756-8757}},\n  journal      = {{TOPICS IN COGNITIVE SCIENCE}},\n  keywords     = {{Routine behavior,Sequence execution,Working memory,Positional code,Task representation,fMRI,Multivariate pattern analysis}},\n  language     = {{eng}},\n  number       = {{2}},\n  pages        = {{223--240}},\n  title        = {{Neural representations of task context and temporal order during action sequence execution}},\n  url          = {{http://doi.org/10.1111/tops.12533}},\n  volume       = {{14}},\n  year         = {{2022}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n Introduction to modeling cognitive processes.\n \n \n \n\n\n \n Verguts, Tom\n\n\n \n\n\n\n MIT Press, 2022.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

\n

@book{8728457,\n  abstract     = {{An introduction to computational modeling for cognitive neuroscientists, covering both foundational work and recent developments.\r\n\r\nCognitive neuroscientists need sophisticated conceptual tools to make sense of their field's proliferation of novel theories, methods, and data. Computational modeling is such a tool, enabling researchers to turn theories into precise formulations. This book offers a mathematically gentle and theoretically unified introduction to modeling cognitive processes. Theoretical exercises of varying degrees of difficulty throughout help readers develop their modeling skills.\r\n\r\nAfter a general introduction to cognitive modeling and optimization, the book covers models of decision making; supervised learning algorithms, including Hebbian learning, delta rule, and backpropagation; the statistical model analysis methods of model parameter estimation and model evaluation; the three recent cognitive modeling approaches of reinforcement learning, unsupervised learning, and Bayesian models; and models of social interaction. All mathematical concepts are introduced gradually, with no background in advanced topics required. Hints and solutions for exercises and a glossary follow the main text. All code in the book is Python, with the Spyder editor in the Anaconda environment. A GitHub repository with Python files enables readers to access the computer code used and start programming themselves. The book is suitable as an introduction to modeling cognitive processes for students across a range of disciplines and as a reference for researchers interested in a broad overview.}},\n  author       = {{Verguts, Tom}},\n  isbn         = {{9780262045360}},\n  keywords     = {{modeling}},\n  language     = {{eng}},\n  pages        = {{241}},\n  publisher    = {{MIT Press}},\n  title        = {{Introduction to modeling cognitive processes}},\n  year         = {{2022}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Electrophysiological signatures of hierarchical learning.\n \n \n \n \n\n\n \n Liu, Meng; Dong, W.; Qin, S.; Verguts, T.; and Chen, Q.\n\n\n \n\n\n\n CEREBRAL CORTEX, 32(3): 626–639. 2022.\n \n\n\n\n
\n\n\n\n \n \n $\"Electrophysiological$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8728459,\n  abstract     = {{Human perception and learning is thought to rely on a hierarchical generative model that is continuously updated via precision-weighted prediction errors (pwPEs). However, the neural basis of such cognitive process and how it unfolds during decision-making remain poorly understood. To investigate this question, we combined a hierarchical Bayesian model (i.e., Hierarchical Gaussian Filter [HGF]) with electroencephalography (EEG), while participants performed a probabilistic reversal learning task in alternatingly stable and volatile environments. Behaviorally, the HGF fitted significantly better than two control, nonhierarchical, models. Neurally, low-level and high-level pwPEs were independently encoded by the P300 component. Low-level pwPEs were reflected in the theta (4-8 Hz) frequency band, but high-level pwPEs were not. Furthermore, the expressions of high-level pwPEs were stronger for participants with better HGF fit. These results indicate that the brain employs hierarchical learning and encodes both low- and high-level learning signals separately and adaptively.}},\n  author       = {{Liu, Meng and Dong, Wenshan and Qin, Shaozheng and Verguts, Tom and Chen, Qi}},\n  issn         = {{1047-3211}},\n  journal      = {{CEREBRAL CORTEX}},\n  keywords     = {{Cognitive Neuroscience,computational modeling,EEG,hierarchical learning,precision-weighted prediction error,PREDICTION ERRORS,ANTERIOR CINGULATE,FRONTAL THETA,NEURAL MECHANISMS,BEHAVIOR,NEGATIVITY,MIDBRAIN,FEEDBACK,CORTEX,MODEL}},\n  language     = {{eng}},\n  number       = {{3}},\n  pages        = {{626--639}},\n  title        = {{Electrophysiological signatures of hierarchical learning}},\n  url          = {{http://doi.org/10.1093/cercor/bhab245}},\n  volume       = {{32}},\n  year         = {{2022}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Using top-down modulation to optimally balance shared versus separated task representations.\n \n \n \n \n\n\n \n Verbeke, Pieter; and Verguts, T.\n\n\n \n\n\n\n NEURAL NETWORKS, 146: 256–271. 2022.\n \n\n\n\n
\n\n\n\n \n \n $\"Using$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8728851,\n  abstract     = {{Human adaptive behavior requires continually learning and performing a wide variety of tasks, often with very little practice. To accomplish this, it is crucial to separate neural representations of different tasks in order to avoid interference. At the same time, sharing neural representations supports generalization and allows faster learning. Therefore, a crucial challenge is to find an optimal balance between shared versus separated representations. Typically, models of human cognition employ top-down modulatory signals to separate task representations, but there exist surprisingly little systematic computational investigations of how such modulation is best implemented. We identify and systematically evaluate two crucial features of modulatory signals. First, top-down input can be processed in an additive or multiplicative manner. Second, the modulatory signals can be adaptive (learned) or non-adaptive (random). We cross these two features, resulting in four modulation networks which are tested on a variety of input datasets and tasks with different degrees of stimulus-action mapping overlap. The multiplicative adaptive modulation network outperforms all other networks in terms of accuracy. Moreover, this network develops hidden units that optimally share representations between tasks. Specifically, different than the binary approach of currently popular latent state models, it exploits partial overlap between tasks.}},\n  author       = {{Verbeke, Pieter and Verguts, Tom}},\n  issn         = {{0893-6080}},\n  journal      = {{NEURAL NETWORKS}},\n  keywords     = {{Artificial Intelligence,Cognitive Neuroscience,Cognitive control,Modulation,Neural representations,Generalization,COMPLEMENTARY LEARNING-SYSTEMS,COMPUTATIONAL MODEL,ANTERIOR CINGULATE,PREFRONTAL CORTEX,COGNITIVE CONTROL,INTEGRATIVE THEORY,GAIN,COMMUNICATION,HIPPOCAMPUS,MODULARITY}},\n  language     = {{eng}},\n  pages        = {{256--271}},\n  title        = {{Using top-down modulation to optimally balance shared versus separated task representations}},\n  url          = {{http://doi.org/10.1016/j.neunet.2021.11.030}},\n  volume       = {{146}},\n  year         = {{2022}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Time-based binding as a solution to and a limitation for flexible cognition.\n \n \n \n \n\n\n \n Senoussi, Mehdi; Verbeke, P.; and Verguts, T.\n\n\n \n\n\n\n FRONTIERS IN PSYCHOLOGY, 12: 13. 2022.\n \n\n\n\n
\n\n\n\n \n \n $\"Time-based$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8735180,\n  abstract     = {{Why can't we keep as many items as we want in working memory? It has long been debated whether this resource limitation is a bug (a downside of our fallible biological system) or instead a feature (an optimal response to a computational problem). We propose that the resource limitation is a consequence of a useful feature. Specifically, we propose that flexible cognition requires time-based binding, and time-based binding necessarily limits the number of (bound) memoranda that can be stored simultaneously. Time-based binding is most naturally instantiated via neural oscillations, for which there exists ample experimental evidence. We report simulations that illustrate this theory and that relate it to empirical data. We also compare the theory to several other (feature and bug) resource theories.}},\n  articleno    = {{798061}},\n  author       = {{Senoussi, Mehdi and Verbeke, Pieter and Verguts, Tom}},\n  issn         = {{1664-1078}},\n  journal      = {{FRONTIERS IN PSYCHOLOGY}},\n  keywords     = {{resources,binding,working memory,oscillations,modeling,simulations,cognitive flexibility,WORKING-MEMORY,ANTERIOR CINGULATE,PREFRONTAL CORTEX,NEURONAL OSCILLATIONS,THETA,ATTENTION,REPRESENTATIONS,MODEL,COMMUNICATION,PERCEPTION}},\n  language     = {{eng}},\n  pages        = {{13}},\n  title        = {{Time-based binding as a solution to and a limitation for flexible cognition}},\n  url          = {{http://doi.org/10.3389/fpsyg.2021.798061}},\n  volume       = {{12}},\n  year         = {{2022}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Thunderstruck : the ACDC model of flexible sequences and rhythms in recurrent neural circuits.\n \n \n \n \n\n\n \n Buc Calderon, Cristian; Verguts, T.; and Frank, M. J.\n\n\n \n\n\n\n PLOS COMPUTATIONAL BIOLOGY, 18(2): 33. 2022.\n \n\n\n\n
\n\n\n\n \n \n $\"Thunderstruck$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8745539,\n  abstract     = {{Adaptive sequential behavior is a hallmark of human cognition. In particular, humans can learn to produce precise spatiotemporal sequences given a certain context. For instance, musicians can not only reproduce learned action sequences in a context-dependent manner, they can also quickly and flexibly reapply them in any desired tempo or rhythm without overwriting previous learning. Existing neural network models fail to account for these properties. We argue that this limitation emerges from the fact that sequence information (i.e., the position of the action) and timing (i.e., the moment of response execution) are typically stored in the same neural network weights. Here, we augment a biologically plausible recurrent neural network of cortical dynamics to include a basal ganglia-thalamic module which uses reinforcement learning to dynamically modulate action. This "associative cluster-dependent chain" (ACDC) model modularly stores sequence and timing information in distinct loci of the network. This feature increases computational power and allows ACDC to display a wide range of temporal properties (e.g., multiple sequences, temporal shifting, rescaling, and compositionality), while still accounting for several behavioral and neurophysiological empirical observations. Finally, we apply this ACDC network to show how it can learn the famous "Thunderstruck" song intro and then flexibly play it in a "bossa nova" rhythm without further training.}},\n  articleno    = {{e1009854}},\n  author       = {{Buc Calderon, Cristian and Verguts, Tom and Frank, Michael J.}},\n  issn         = {{1553-734X}},\n  journal      = {{PLOS COMPUTATIONAL BIOLOGY}},\n  keywords     = {{SHORT-TERM-MEMORY,DISTAL REWARD PROBLEM,BASAL GANGLIA,WORKING-MEMORY,COMPUTATIONAL MODEL,PREFRONTAL CORTEX,DECISION-MAKING,TEMPORAL ORGANIZATION,SUBTHALAMIC NUCLEUS,PERSISTENT ACTIVITY}},\n  language     = {{eng}},\n  number       = {{2}},\n  pages        = {{33}},\n  title        = {{Thunderstruck : the ACDC model of flexible sequences and rhythms in recurrent neural circuits}},\n  url          = {{http://doi.org/10.1371/journal.pcbi.1009854}},\n  volume       = {{18}},\n  year         = {{2022}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Theta oscillations shift towards optimal frequency for cognitive control.\n \n \n \n \n\n\n \n Senoussi, Mehdi; Verbeke, P.; Desender, K.; De Loof, E.; Talsma, D.; and Verguts, T.\n\n\n \n\n\n\n NATURE HUMAN BEHAVIOUR, 6(7): 1000–1013. 2022.\n \n\n\n\n
\n\n\n\n \n \n $\"Theta$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8750041,\n  abstract     = {{Cognitive control allows to flexibly guide behaviour in a complex and ever-changing environment. It is supported by theta band (4-7 Hz) neural oscillations that coordinate distant neural populations. However, little is known about the precise neural mechanisms permitting such flexible control. Most research has focused on theta amplitude, showing that it increases when control is needed, but a second essential aspect of theta oscillations, their peak frequency, has mostly been overlooked. Here, using computational modelling and behavioural and electrophysiological recordings, in three independent datasets, we show that theta oscillations adaptively shift towards optimal frequency depending on task demands. We provide evidence that theta frequency balances reliable set-up of task representation and gating of task-relevant sensory and motor information and that this frequency shift predicts behavioural performance. Our study presents a mechanism supporting flexible control and calls for a reevaluation of the mechanistic role of theta oscillations in adaptive behaviour.\r\n\r\nSenoussi et al. present modelling, behavioural and neural evidence that frontal theta oscillations (4-7 Hz) shift their peak frequency in response to task demands to support flexible task implementation.}},\n  author       = {{Senoussi, Mehdi and Verbeke, Pieter and Desender, Kobe and De Loof, Esther and Talsma, Durk and Verguts, Tom}},\n  issn         = {{2397-3374}},\n  journal      = {{NATURE HUMAN BEHAVIOUR}},\n  keywords     = {{MEDIAL FRONTAL-CORTEX,ANTERIOR CINGULATE,NEURAL MECHANISMS,SUSTAINED ATTENTION,GAMMA-OSCILLATIONS,PHASE SYNCHRONY,PEAK FREQUENCY,MIDLINE THETA,POWER SPECTRA,EEG ALPHA}},\n  language     = {{eng}},\n  number       = {{7}},\n  pages        = {{1000--1013}},\n  title        = {{Theta oscillations shift towards optimal frequency for cognitive control}},\n  url          = {{http://doi.org/10.1038/s41562-022-01335-5}},\n  volume       = {{6}},\n  year         = {{2022}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Imbalance between the caudate and putamen connectivity in obsessive-compulsive disorder.\n \n \n \n \n\n\n \n Peng, Ziwen; He, T.; Ren, P.; Jin, L.; Yang, Q.; Xu, C.; Wen, R.; Chen, J.; Wei, Z.; Verguts, T.; and Chen, Q.\n\n\n \n\n\n\n NEUROIMAGE-CLINICAL, 35: 8. 2022.\n \n\n\n\n
\n\n\n\n \n \n $\"Imbalance$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8761981,\n  abstract     = {{Background: Compulsive behaviors in obsessive-compulsive disorder (OCD) have been suggested to result from an imbalance in cortico-striatal connectivity. However, the nature of this impairment, the relative involvement of different striatal areas, their imbalance in genetically related but unimpaired individuals, and their relationship with cognitive dysfunction in OCD patients, remain unknown. Methods: In the current study, striatal (i.e., caudate and putamen) whole-brain connectivity was computed in a sample of OCD patients (OCD, n = 62), unaffected first-degree relatives (UFDR, n = 53) and healthy controls (HC, n = 73) by ROI-based resting-state functional magnetic resonance imaging (rs-fMRI). A behavioral task switch paradigm outside of the scanner was also performed to measure cognitive flexibility in OCD patients. Results: There were significantly increased strengths (Z-transformed Pearson correlation coefficient) in caudate connectivity in OCD patients. A significant correlation between the two types of connectivity strengths in the relevant regions was observed only in the OCD patient group. Furthermore, the caudate connectivity of patients was negatively associated with their task-switch performance. Conclusions: The imbalance between the caudate and putamen connectivity, arising from the abnormal increase of caudate activity, may serve as a clinical characteristic for obsessive-compulsive disorder.}},\n  articleno    = {{103083}},\n  author       = {{Peng, Ziwen and He, Tingxin and Ren, Ping and Jin, Lili and Yang, Qiong and Xu, Chuanyong and Wen, Rongzhen and Chen, Jierong and Wei, Zhen and Verguts, Tom and Chen, Qi}},\n  issn         = {{2213-1582}},\n  journal      = {{NEUROIMAGE-CLINICAL}},\n  keywords     = {{Obsessive-compulsive disorder (OCD),Functional connectivity,Caudate connectivity,Putamen connectivity,GOAL-DIRECTED BEHAVIOR,BASAL GANGLIA,COGNITIVE FLEXIBILITY,BRAIN ACTIVATION,AVOIDANCE HABITS,REWARD,STRIATUM,ADULTS,PROVOCATION,DISRUPTION}},\n  language     = {{eng}},\n  pages        = {{8}},\n  title        = {{Imbalance between the caudate and putamen connectivity in obsessive-compulsive disorder}},\n  url          = {{http://doi.org/10.1016/j.nicl.2022.103083}},\n  volume       = {{35}},\n  year         = {{2022}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Dynamic influences on static measures of metacognition.\n \n \n \n \n\n\n \n Desender, Kobe; Vermeylen, L.; and Verguts, T.\n\n\n \n\n\n\n NATURE COMMUNICATIONS, 13: 12. 2022.\n \n\n\n\n
\n\n\n\n \n \n $\"Dynamic$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8762199,\n  abstract     = {{Humans differ in their capability to judge choice accuracy via confidence judgments. Popular signal detection theoretic measures of metacognition, such as M-ratio, do not consider the dynamics of decision making. This can be problematic if response caution is shifted to alter the tradeoff between speed and accuracy. Such shifts could induce unaccounted-for sources of variation in the assessment of metacognition. Instead, evidence accumulation frameworks consider decision making, including the computation of confidence, as a dynamic process unfolding over time. Using simulations, we show a relation between response caution and M-ratio. We then show the same pattern in human participants explicitly instructed to focus on speed or accuracy. Finally, this association between M-ratio and response caution is also present across four datasets without any reference towards speed. In contrast, when data are analyzed with a dynamic measure of metacognition, v-ratio, there is no effect of speed-accuracy tradeoff.}},\n  articleno    = {{4208}},\n  author       = {{Desender, Kobe and Vermeylen, Luc and Verguts, Tom}},\n  issn         = {{2041-1723}},\n  journal      = {{NATURE COMMUNICATIONS}},\n  keywords     = {{General Physics and Astronomy,General Biochemistry,Genetics and Molecular Biology,General Chemistry,Multidisciplinary,SIGNAL-DETECTION,DECISION-MAKING,CONFIDENCE,ACCURACY,PERFORMANCE,JUDGMENTS,CLOSURE,MODELS,CHOICE,MEMORY}},\n  language     = {{eng}},\n  pages        = {{12}},\n  title        = {{Dynamic influences on static measures of metacognition}},\n  url          = {{http://doi.org/10.1038/s41467-022-31727-0}},\n  volume       = {{13}},\n  year         = {{2022}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Obsessive-compulsive disorder is characterized by decreased Pavlovian influence on instrumental behavior.\n \n \n \n \n\n\n \n Peng, Ziwen; He, L.; Wen, R.; Verguts, T.; Seger, C. A.; and Chen, Q.\n\n\n \n\n\n\n PLOS COMPUTATIONAL BIOLOGY, 18(10): 22. 2022.\n \n\n\n\n
\n\n\n\n \n \n $\"Obsessive-compulsive$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{01GKC4MJDN745580JQHJJ5ANH1,\n  abstract     = {{Obsessive-compulsive disorder (OCD) is characterized by uncontrollable repetitive actions thought to rely on abnormalities within fundamental instrumental learning systems. We investigated cognitive and computational mechanisms underlying Pavlovian biases on instrumental behavior in both clinical OCD patients and healthy controls using a Pavlovian-Instrumental Transfer (PIT) task. PIT is typically evidenced by increased responding in the presence of a positive (previously rewarded) Pavlovian cue, and reduced responding in the presence of a negative cue. Thirty OCD patients and thirty-one healthy controls completed the Pavlovian Instrumental Transfer test, which included instrumental training, Pavlovian training for positive, negative and neutral cues, and a PIT phase in which participants performed the instrumental task in the presence of the Pavlovian cues. Modified Rescorla-Wagner models were fitted to trial-by-trial data of participants to estimate underlying computational mechanism and quantify individual differences during training and transfer stages. Bayesian hierarchical methods were used to estimate free parameters and compare the models. Behavioral and computational results indicated a weaker Pavlovian influence on instrumental behavior in OCD patients than in HC, especially for negative Pavlovian cues. Our results contrast with the increased PIT effects reported for another set of disorders characterized by compulsivity, substance use disorders, in which PIT is enhanced. A possible reason for the reduced PIT in OCD may be impairment in using the contextual information provided by the cues to appropriately adjust behavior, especially when inhibiting responding when a negative cue is present. This study provides deeper insight into our understanding of deficits in OCD from the perspective of Pavlovian influences on instrumental behavior and may have implications for OCD treatment modalities focused on reducing compulsive behaviors.}},\n  articleno    = {{e1009945}},\n  author       = {{Peng, Ziwen and He, Luning and Wen, Rongzhen and Verguts, Tom and Seger, Carol A. and Chen, Qi}},\n  issn         = {{1553-734X}},\n  journal      = {{PLOS COMPUTATIONAL BIOLOGY}},\n  keywords     = {{Computational Theory and Mathematics,Cellular and Molecular Neuroscience,Genetics,Molecular Biology,Ecology,Modeling and Simulation,Ecology, Evolution, Behavior and Systematics}},\n  language     = {{eng}},\n  number       = {{10}},\n  pages        = {{22}},\n  title        = {{Obsessive-compulsive disorder is characterized by decreased Pavlovian influence on instrumental behavior}},\n  url          = {{http://doi.org/10.1371/journal.pcbi.1009945}},\n  volume       = {{18}},\n  year         = {{2022}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Computational investigations of learning and synchronization in cognitive control.\n \n \n \n \n\n\n \n Huycke, Pieter; Lesage, E.; Böhler, N.; and Verguts, T.\n\n\n \n\n\n\n JOURNAL OF COGNITION, 5(1): 20. 2022.\n \n\n\n\n
\n\n\n\n \n \n $\"Computational$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{01GKC43E7VNN6RZJSRFVXPK9MZ,\n  abstract     = {{Complex cognition requires binding together of stimulus, action, and other features, across different time scales. Several implementations of such binding have been proposed in the literature, most prominently synaptic binding (learning) and synchronization. Biologically plausible accounts of how these different types of binding interact in the human brain are still lacking. To this end, we adopt a computational approach to investigate the impact of learning and synchronization on both behavioral (reaction time, error rate) and neural (θ power) measures. We train four models varying in their ability to learn and synchronize for an extended period of time on three seminal action control paradigms varying in difficulty. Learning, but not synchronization, proved essential for behavioral improvement. Synchronization however boosts performance of difficult tasks, avoiding the computational pitfalls of catastrophic interference. At the neural level, θ power decreases with practice but increases with task difficulty. Our simulation results bring new insights in how different types of binding interact in different types of tasks, and how this is translated in both behavioral and neural metrics.}},\n  articleno    = {{44}},\n  author       = {{Huycke, Pieter and Lesage, Elise and Böhler, Nico and Verguts, Tom}},\n  issn         = {{2514-4820}},\n  journal      = {{JOURNAL OF COGNITION}},\n  language     = {{eng}},\n  number       = {{1}},\n  pages        = {{20}},\n  title        = {{Computational investigations of learning and synchronization in cognitive control}},\n  url          = {{http://doi.org/10.5334/joc.239}},\n  volume       = {{5}},\n  year         = {{2022}},\n}\n\n

\n

\n\n\n\n\n\n

\n

\n \n 2021\n \n \n (12)\n \n \n

\n

\n \n \n

\n \n\n \n \n \n \n \n \n Spatial attention in serial order working memory : an EEG study.\n \n \n \n \n\n\n \n Rasoulzadeh, Vesal; Sahan, M. I.; van Dijck, J.; Abrahamse, E.; Marzecova, A.; Verguts, T.; and Fias, W.\n\n\n \n\n\n\n CEREBRAL CORTEX, 31(5): 2482–2493. 2021.\n \n\n\n\n
\n\n\n\n \n \n $\"Spatial$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8684602,\n  abstract     = {{Theoretical models explaining serial order processing link order information to specified position markers. However, the precise characteristics of position marking have remained largely elusive. Recent studies have shown that space is involved in marking serial position of items in verbal working memory (WM). Furthermore, it has been suggested, but not proven, that accessing these items involves horizontal shifts of spatial attention. We used continuous electroencephalography recordings to show that memory search in serial order verbal WM involves spatial attention processes that share the same electrophysiological signatures as those operating on the visuospatial WM and external space. Accessing an item from a sequence in verbal WM induced posterior “early directing attention negativity” and “anterior directing attention negativity” contralateral to the position of the item in mental space (i.e., begin items on the left; end items on the right). In the frequency domain, we observed posterior alpha suppression contralateral to the position of the item. Our results provide clear evidence for the involvement of spatial attention in retrieving serial information from verbal WM. Implications for WM models are discussed.}},\n  author       = {{Rasoulzadeh, Vesal and Sahan, Muhammet Ikbal and van Dijck, Jean-Philippe and Abrahamse, Elger and Marzecova, Anna and Verguts, Tom and Fias, Wim}},\n  issn         = {{1047-3211}},\n  journal      = {{CEREBRAL CORTEX}},\n  keywords     = {{ADAN,alpha oscillations,EDAN,spatial attention,verbal working memory,SHORT-TERM-MEMORY,MECHANISMS,MODEL,INFORMATION,DYNAMICS,ERP,OSCILLATIONS,LOCATIONS,COMPONENT,PARIETAL}},\n  language     = {{eng}},\n  number       = {{5}},\n  pages        = {{2482--2493}},\n  title        = {{Spatial attention in serial order working memory : an EEG study}},\n  url          = {{http://doi.org/10.1093/cercor/bhaa368}},\n  volume       = {{31}},\n  year         = {{2021}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Learning to synchronize : midfrontal theta dynamics during rule switching.\n \n \n \n \n\n\n \n Verbeke, Pieter; Ergo, K.; De Loof, E.; and Verguts, T.\n\n\n \n\n\n\n JOURNAL OF NEUROSCIENCE, 41(7): 1516–1528. 2021.\n \n\n\n\n
\n\n\n\n \n \n $\"Learning$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8687585,\n  abstract     = {{In recent years, several hierarchical extensions of well-known learning algorithms have been proposed. For example, when stimulus-action mappings vary across time or context, the brain may learn two or more stimulus-action mappings in separate modules, and additionally (at a hierarchically higher level) learn to appropriately switch between those modules. However, how the brain mechanistically coordinates neural communication to implement such hierarchical learning remains unknown. Therefore, the current study tests a recent computational model that proposed how midfrontal theta oscillations implement such hierarchical learning via the principle of binding by synchrony (Sync model). More specifically, the Sync model uses bursts at theta frequency to flexibly bind appropriate task modules by synchrony. The 64-channel EEG signal was recorded while 27 human subjects (female: 21, male: 6) performed a probabilistic reversal learning task. In line with the Sync model, postfeedback theta power showed a linear relationship with negative prediction errors, but not with positive prediction errors. This relationship was especially pronounced for subjects with better behavioral fit (measured via Akaike information criterion) of the Sync model. Also consistent with Sync model simulations, theta phase-coupling between midfrontal electrodes and temporoparietal electrodes was stronger after negative feedback. Our data suggest that the brain uses theta power and synchronization for flexibly switching between task rule modules, as is useful, for example, when multiple stimulus action mappings must be retained and used.}},\n  author       = {{Verbeke, Pieter and Ergo, Kate and De Loof, Esther and Verguts, Tom}},\n  issn         = {{0270-6474}},\n  journal      = {{JOURNAL OF NEUROSCIENCE}},\n  keywords     = {{General Neuroscience,cognitive control,midfrontal theta,neural synchrony,rule switching,ANTERIOR CINGULATE CORTEX,COGNITIVE CONTROL,COMPUTATIONAL MODEL,PHASE SYNCHRONY,FRONTAL THETA,EEG-DATA,COMMUNICATION,OSCILLATIONS,MECHANISM,ERROR}},\n  language     = {{eng}},\n  number       = {{7}},\n  pages        = {{1516--1528}},\n  title        = {{Learning to synchronize : midfrontal theta dynamics during rule switching}},\n  url          = {{http://doi.org/10.1523/jneurosci.1874-20.2020}},\n  volume       = {{41}},\n  year         = {{2021}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Autistic traits are related to worse performance in a volatile reward learning task despite adaptive learning rates.\n \n \n \n \n\n\n \n Goris, Judith; Silvetti, M.; Verguts, T.; Wiersema, R.; Brass, M.; and Braem, S.\n\n\n \n\n\n\n AUTISM, 25(2): 1362361320962237:440–1362361320962237:451. 2021.\n \n\n\n\n
\n\n\n\n \n \n $\"Autistic$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8692667,\n  abstract     = {{Recent theories propose that autism is characterized by an impairment in determining when to learn and when not. We investigated this by estimating learning rate in environments varying in volatility and uncertainty. Specifically, we correlated autistic traits (in 163 neurotypical participants) with modelled learning behaviour during probabilistic reward learning under the following three conditions: a Stationary Low Noise condition with stable reward contingencies, a Volatile condition with changing reward contingencies and a Stationary High Noise condition where reward probabilities for all options were 60%, resulting in an uncertain, noisy environment. Consistent with earlier findings, we found less optimal decision-making in the Volatile condition for participants with more autistic traits. However, we observed no correlations between underlying adjustments in learning rates and autistic traits, suggesting no impairment in updating learning rates in response to volatile versus noisy environments. Exploratory analyses indicated that impaired performance in the Volatile condition in participants with more autistic traits, was specific to trials with reward contingencies opposite to those initially learned, suggesting a primacy bias. We conclude that performance in volatile environments is lower in participants with more autistic traits, but this cannot be unambiguously attributed to difficulties with adjusting learning rates. Lay abstract Recent theories propose that autism is characterized by an impairment in determining when to learn and when not. Here, we investigated this hypothesis by estimating learning rates (i.e. the speed with which one learns) in three different environments that differed in rule stability and uncertainty. We found that neurotypical participants with more autistic traits performed worse in a volatile environment (with unstable rules), as they chose less often for the most rewarding option. Exploratory analyses indicated that performance was specifically worse when reward rules were opposite to those initially learned for participants with more autistic traits. However, there were no differences in the adjustment of learning rates between participants with more versus less autistic traits. Together, these results suggest that performance in volatile environments is lower in participants with more autistic traits, but that this performance difference cannot be unambiguously explained by an impairment in adjusting learning rates.}},\n  articleno    = {{1362361320962237}},\n  author       = {{Goris, Judith and Silvetti, Massimo and Verguts, Tom and Wiersema, Roeljan and Brass, Marcel and Braem, Senne}},\n  issn         = {{1362-3613}},\n  journal      = {{AUTISM}},\n  keywords     = {{SPECTRUM QUOTIENT AQ,FUNCTIONING AUTISM,GENERAL-POPULATION,DECISION-MAKING,ADULTS,SENSITIVITY,VALIDITY,DISORDER,WORLD,autism spectrum disorders,learning rate,reward decision-making}},\n  language     = {{eng}},\n  number       = {{2}},\n  pages        = {{1362361320962237:440--1362361320962237:451}},\n  title        = {{Autistic traits are related to worse performance in a volatile reward learning task despite adaptive learning rates}},\n  url          = {{http://doi.org/10.1177/1362361320962237}},\n  volume       = {{25}},\n  year         = {{2021}},\n}\n\n

\n

\n\n\n

\n Recent theories propose that autism is characterized by an impairment in determining when to learn and when not. We investigated this by estimating learning rate in environments varying in volatility and uncertainty. Specifically, we correlated autistic traits (in 163 neurotypical participants) with modelled learning behaviour during probabilistic reward learning under the following three conditions: a Stationary Low Noise condition with stable reward contingencies, a Volatile condition with changing reward contingencies and a Stationary High Noise condition where reward probabilities for all options were 60%, resulting in an uncertain, noisy environment. Consistent with earlier findings, we found less optimal decision-making in the Volatile condition for participants with more autistic traits. However, we observed no correlations between underlying adjustments in learning rates and autistic traits, suggesting no impairment in updating learning rates in response to volatile versus noisy environments. Exploratory analyses indicated that impaired performance in the Volatile condition in participants with more autistic traits, was specific to trials with reward contingencies opposite to those initially learned, suggesting a primacy bias. We conclude that performance in volatile environments is lower in participants with more autistic traits, but this cannot be unambiguously attributed to difficulties with adjusting learning rates. Lay abstract Recent theories propose that autism is characterized by an impairment in determining when to learn and when not. Here, we investigated this hypothesis by estimating learning rates (i.e. the speed with which one learns) in three different environments that differed in rule stability and uncertainty. We found that neurotypical participants with more autistic traits performed worse in a volatile environment (with unstable rules), as they chose less often for the most rewarding option. Exploratory analyses indicated that performance was specifically worse when reward rules were opposite to those initially learned for participants with more autistic traits. However, there were no differences in the adjustment of learning rates between participants with more versus less autistic traits. Together, these results suggest that performance in volatile environments is lower in participants with more autistic traits, but that this performance difference cannot be unambiguously explained by an impairment in adjusting learning rates.\n

\n\n\n

\n \n\n \n \n \n \n \n \n Dynamic expressions of confidence within an evidence accumulation framework.\n \n \n \n \n\n\n \n Desender, Kobe; Donner, T. H.; and Verguts, T.\n\n\n \n\n\n\n COGNITION, 207: 11. 2021.\n \n\n\n\n
\n\n\n\n \n \n $\"Dynamic$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8692718,\n  abstract     = {{Human observers can reliably report their confidence in the choices they make. An influential framework conceptualizes decision confidence as the probability of a decision being correct, given the choice made and the evidence on which it was based. This framework accounts for three diagnostic signatures of human confidence reports, including an opposite dependence of confidence on evidence strength for correct and error trials. However, the framework does not account for the temporal evolution of these signatures, because it only describes the transformation of a static representation of evidence into choice and the associated confidence. Here, we combine this framework with another influential framework: dynamic accumulation of evidence over time, and build on the notion that confidence reflects the probability of being correct, given the choice and accumulated evidence up until that point. Critically, we show that such a dynamic model predicts that the diagnostic signatures of confidence depend on time; most critically, it predicts a stronger opposite dependence of confidence on evidence strength and choice correctness as a function of time. We tested, and confirmed, these predictions in human behaviour during random dot motion discrimination, in which confidence judgments were queried at different points in time. We conclude that human confidence reports reflect the dynamics of the probability of being correct given the accumulated evidence and choice.}},\n  articleno    = {{104522}},\n  author       = {{Desender, Kobe and Donner, Tobias H. and Verguts, Tom}},\n  issn         = {{0010-0277}},\n  journal      = {{COGNITION}},\n  keywords     = {{Linguistics and Language,Experimental and Cognitive Psychology,Cognitive Neuroscience,Developmental and Educational Psychology,Language and Linguistics,Confidence,Decision making,Drift diffusion model,Metacognition,DECISION CONFIDENCE,SIGNAL-DETECTION,CHOICE,COMPUTATION,INTEGRATION,JUDGMENTS,CERTAINTY,MEMORY}},\n  language     = {{eng}},\n  pages        = {{11}},\n  title        = {{Dynamic expressions of confidence within an evidence accumulation framework}},\n  url          = {{http://doi.org/10.1016/j.cognition.2020.104522}},\n  volume       = {{207}},\n  year         = {{2021}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Signed reward prediction errors in the ventral striatum drive episodic memory.\n \n \n \n \n\n\n \n Buc Calderon, Cristian; De Loof, E.; Ergo, K.; Snoeck, A.; Böhler, N.; and Verguts, T.\n\n\n \n\n\n\n JOURNAL OF NEUROSCIENCE, 41(8): 1716–1726. 2021.\n \n\n\n\n
\n\n\n\n \n \n $\"Signed$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8702063,\n  abstract     = {{Recent behavioral evidence implicates reward prediction errors (RPEs) as a key factor in the acquisition of episodic memory. Yet, important neural predictions related to the role of RPEs in episodic memory acquisition remain to be tested. Humans (both sexes) performed a novel variable-choice task where we experimentally manipulated RPEs and found support for key neural predictions with fMRI. Our results show that in line with previous behavioral observations, episodic memory accuracy increases with the magnitude of signed (i.e., better/worse-than-expected) RPEs (SRPEs). Neurally, we observe that SRPEs are encoded in the ventral striatum (VS). Crucially, we demonstrate through mediation analysis that activation in the VS mediates the experimental manipulation of SRPEs on episodic memory accuracy. In particular, SRPE-based responses in the VS (during learning) predict the strength of subsequent episodic memory (during recollection). Furthermore, functional connectivity between task-relevant processing areas (i.e., face-selective areas) and hippocampus and ventral striatum increased as a function of RPE value (during learning), suggesting a central role of these areas in episodic memory formation. Our results consolidate reinforcement learning theory and striatal RPEs as key factors subtending the formation of episodic memory.}},\n  author       = {{Buc Calderon, Cristian and De Loof, Esther and Ergo, Kate and Snoeck, Anna and Böhler, Nico and Verguts, Tom}},\n  issn         = {{0270-6474}},\n  journal      = {{JOURNAL OF NEUROSCIENCE}},\n  keywords     = {{episodic memory,fMRI,reward prediction error,ventral striatum,THETA OSCILLATIONS,ACTIVATION,SIGNALS,FMRI,GLUE}},\n  language     = {{eng}},\n  number       = {{8}},\n  pages        = {{1716--1726}},\n  title        = {{Signed reward prediction errors in the ventral striatum drive episodic memory}},\n  url          = {{http://doi.org/10.1523/JNEUROSCI.1785-20.2020}},\n  volume       = {{41}},\n  year         = {{2021}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Outcome value and task aversiveness impact task procrastination through separate neural pathways.\n \n \n \n \n\n\n \n Zhang, Shunmin; Verguts, T.; Zhang, C.; Feng, P.; Chen, Q.; and Feng, T.\n\n\n \n\n\n\n CEREBRAL CORTEX, 31(8): 3846–3855. 2021.\n \n\n\n\n
\n\n\n\n \n \n $\"Outcome$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8716697,\n  abstract     = {{The temporal decision model of procrastination has proposed that outcome value and task aversiveness are two separate aspects accounting for procrastination. If true, the human brain is likely to implicate separate neural pathways to mediate the effect of outcome value and task aversiveness on procrastination. Outcome value is plausibly constructed via a hippocampus-based pathway because of the hippocampus's unique role in episodic prospection. In contrast, task aversiveness might be represented through an amygdala-involved pathway. In the current study, participants underwent fMRI scanning when viewing both tasks and future outcomes, without any experimental instruction imposed. The results revealed that outcome value increased activations in the caudate, and suppressed procrastination through a hippocampus-caudate pathway. In contrast, task aversiveness increased activations in the anterior insula, and increased procrastination via an amygdala-insula pathway. In sum, this study demonstrates that people can incorporate both outcome value and task aversiveness into task valuation to decide whether to procrastinate or not; and it elucidates the separate neural pathways via which this occurs.}},\n  author       = {{Zhang, Shunmin and Verguts, Tom and Zhang, Chenyan and Feng, Pan and Chen, Qi and Feng, Tingyong}},\n  issn         = {{1047-3211}},\n  journal      = {{CEREBRAL CORTEX}},\n  keywords     = {{amygdale-insula coupling,dual-process theory,hippocampus-striatum coupling,procrastination,task valuation}},\n  language     = {{eng}},\n  number       = {{8}},\n  pages        = {{3846--3855}},\n  title        = {{Outcome value and task aversiveness impact task procrastination through separate neural pathways}},\n  url          = {{http://doi.org/10.1093/cercor/bhab053}},\n  volume       = {{31}},\n  year         = {{2021}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Reward prediction errors drive declarative learning irrespective of agency.\n \n \n \n \n\n\n \n Ergo, Kate; De Vilder, L.; De Loof, E.; and Verguts, T.\n\n\n \n\n\n\n PSYCHONOMIC BULLETIN & REVIEW, 28: 2045–2056. 2021.\n \n\n\n\n
\n\n\n\n \n \n $\"Reward$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8716803,\n  abstract     = {{Recent years have witnessed a steady increase in the number of studies investigating the role of reward prediction errors (RPEs) in declarative learning. Specifically, in several experimental paradigms, RPEs drive declarative learning, with larger and more positive RPEs enhancing declarative learning. However, it is unknown whether this RPE must derive from the participant's own response, or whether instead, any RPE is sufficient to obtain the learning effect. To test this, we generated RPEs in the same experimental paradigm where we combined an agency and a nonagency condition. We observed no interaction between RPE and agency, suggesting that any RPE (irrespective of its source) can drive declarative learning. This result holds implications for declarative learning theory.}},\n  author       = {{Ergo, Kate and De Vilder, Luna and De Loof, Esther and Verguts, Tom}},\n  issn         = {{1069-9384}},\n  journal      = {{PSYCHONOMIC BULLETIN & REVIEW}},\n  keywords     = {{Agency,Declarative learning,Memory,Reward prediction error}},\n  language     = {{eng}},\n  pages        = {{2045--2056}},\n  title        = {{Reward prediction errors drive declarative learning irrespective of agency}},\n  url          = {{http://doi.org/10.3758/s13423-021-01952-7}},\n  volume       = {{28}},\n  year         = {{2021}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Theta and alpha power across fast and slow timescales in cognitive control.\n \n \n \n \n\n\n \n Huycke, Pieter; Verbeke, P.; Böhler, N.; and Verguts, T.\n\n\n \n\n\n\n EUROPEAN JOURNAL OF NEUROSCIENCE, 54(2): 4581–4594. 2021.\n \n\n\n\n
\n\n\n\n \n \n $\"Theta$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8717759,\n  abstract     = {{Theta and alpha frequency neural oscillations are important for learning and cognitive control, but their exact role has remained obscure. In particular, it is unknown whether they operate at similar timescales, and whether they support different cognitive processes. We recorded EEG in 30 healthy human participants while they performed a learning task containing both novel (block-unique) and repeating stimuli. We investigated behavior and electrophysiology at both fast (i.e., within blocks) and slow (i.e., between blocks) timescales. Behaviorally, both response time and accuracy improved (respectively decrease and increase) over both fast and slow timescales. However, on the spectral level, theta power significantly decreased along the slow timescale, whereas alpha power significantly increased along the fast timescale. We thus demonstrate that theta and alpha both play a role during learning, but operate at different timescales. This result poses important empirical constraints for theories on learning, cognitive control, and neural oscillations.}},\n  author       = {{Huycke, Pieter and Verbeke, Pieter and Böhler, Nico and Verguts, Tom}},\n  issn         = {{0953-816X}},\n  journal      = {{EUROPEAN JOURNAL OF NEUROSCIENCE}},\n  keywords     = {{General Neuroscience,cognitive control,frontomedial theta,learning,posterior alpha,FRONTAL-MIDLINE THETA,EEG-ALPHA,PREFRONTAL CORTEX,OSCILLATIONS,DYNAMICS,PERFORMANCE,BAND,SYNCHRONIZATION,MODULATION,AMPLITUDE}},\n  language     = {{eng}},\n  number       = {{2}},\n  pages        = {{4581--4594}},\n  title        = {{Theta and alpha power across fast and slow timescales in cognitive control}},\n  url          = {{http://doi.org/10.1111/ejn.15320}},\n  volume       = {{54}},\n  year         = {{2021}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n The best laid plans : computational principles of anterior cingulate cortex.\n \n \n \n \n\n\n \n Holroyd, Clay; and Verguts, T.\n\n\n \n\n\n\n TRENDS IN COGNITIVE SCIENCES, 25(4): 316–329. 2021.\n \n\n\n\n
\n\n\n\n \n \n $\"The$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{8719049,\n  abstract     = {{Despite continual debate for the past 30 years about the function of anterior cingulate cortex (ACC), its key contribution to neurocognition remains unknown. However, recent computational modeling work has provided insight into this question. Here we review computational models that illustrate three core principles of ACC function, related to hierarchy, world models, and cost. We also discuss four constraints on the neural implementation of these principles, related to modularity, binding, encoding, and learning and regulation. These observations suggest a role for ACC in hierarchical model-based hierarchical reinforcement learning (HMB-HRL), which instantiates a mechanism motivating the execution of high-level plans.}},\n  author       = {{Holroyd, Clay and Verguts, Tom}},\n  issn         = {{1364-6613}},\n  journal      = {{TRENDS IN COGNITIVE SCIENCES}},\n  language     = {{eng}},\n  number       = {{4}},\n  pages        = {{316--329}},\n  title        = {{The best laid plans : computational principles of anterior cingulate cortex}},\n  url          = {{http://doi.org/10.1016/j.tics.2021.01.008}},\n  volume       = {{25}},\n  year         = {{2021}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n White matter alterations of the goal-directed system in patients with obsessive-compulsive disorder and their unaffected first-degree relatives.\n \n \n \n \n\n\n \n Peng, Ziwen; Xu, C.; Ma, N.; Yang, Q.; Ren, P.; Wen, R.; Jin, L.; Chen, J.; Wei, Z.; Verguts, T.; and Chen, Q.\n\n\n \n\n\n\n BIOLOGICAL PSYCHIATRY-COGNITIVE NEUROSCIENCE AND NEUROIMAGING, 6(10): 992–1001. 2021.\n \n\n\n\n
\n\n\n\n \n \n $\"White$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8724748,\n  abstract     = {{BACKGROUND: It has been postulated that the neurobiological mechanism responsible for the onset of symptoms of obsessive-compulsive disorder (OCD), especially compulsive behavior, is related to alterations of the goal-directed and habitual learning systems. However, little is known about whether changes in these learning systems cooccur with changes in the white matter structure of patients with OCD and their unaffected first-degree relatives (UFDRs). METHODS: Diffusion tensor imaging data were acquired from 32 patients with OCD (21 male), 32 UFDRs (16 male), and 32 healthy control subjects (16 male). White matter tracts in the goal-directed and habitual networks were reconstructed with seed-based probabilistic tractography. Partial least squares path modeling was used to measure the covariation between white matter connectivity, psychiatric symptoms, and cognitive flexibility. RESULTS: Patients with OCD showed reduced connectivity in the fiber tracts within the goal-directed but not within the habitual network compared with healthy control subjects. Using partial least squares path modeling, patients' symptoms were negatively associated with connectivity within the goal-directed but not within the habitual network. Cognitive flexibility was correlated negatively with caudate-dorsolateral prefrontal cortex tracts in patients with OCD. UFDRs also exhibited reduced white matter connectivity in the goal-directed network. CONCLUSIONS: These findings suggest that the balance of learning systems in OCD may be disrupted, mainly impairing white matter in the goal-directed network. Alterations of the goal-directed network could explain overt symptoms and impaired cognitive flexibility in patients with OCD. Similar alterations in the goal-directed network are present in UFDRs. The impaired goal-directed system may be an endophenotype of OCD.}},\n  author       = {{Peng, Ziwen and Xu, Chuanyong and Ma, Ning and Yang, Qiong and Ren, Ping and Wen, Rongzhen and Jin, Lili and Chen, Jierong and Wei, Zhen and Verguts, Tom and Chen, Qi}},\n  issn         = {{2451-9022}},\n  journal      = {{BIOLOGICAL PSYCHIATRY-COGNITIVE NEUROSCIENCE AND NEUROIMAGING}},\n  keywords     = {{TOPOGRAPHICAL ORGANIZATION,STRUCTURAL CONNECTIVITY,RESPONSE-INHIBITION,SYMPTOM DIMENSIONS,NUCLEUS-ACCUMBENS,AVOIDANCE,HABITS,CIRCUITS,BEHAVIOR,CORTEX,ENDOPHENOTYPES}},\n  language     = {{eng}},\n  number       = {{10}},\n  pages        = {{992--1001}},\n  title        = {{White matter alterations of the goal-directed system in patients with obsessive-compulsive disorder and their unaffected first-degree relatives}},\n  url          = {{http://doi.org/10.1016/j.bpsc.2020.12.004}},\n  volume       = {{6}},\n  year         = {{2021}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Aberrant rich club organization in patients with obsessive-compulsive disorder and their unaffected first-degree relatives.\n \n \n \n \n\n\n \n Peng, Ziwen; Yang, X.; Xu, C.; Wu, X.; Yang, Q.; Wei, Z.; Zhou, Z.; Verguts, T.; and Chen, Q.\n\n\n \n\n\n\n NEUROIMAGE-CLINICAL, 32: 9. 2021.\n \n\n\n\n
\n\n\n\n \n \n $\"Aberrant$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8725679,\n  abstract     = {{Recent studies suggested that the rich club organization promoting global brain communication and integration of information, may be abnormally increased in obsessive-compulsive disorder (OCD). However, the structural and functional basis of this organization is still not very clear. Given the heritability of OCD, as suggested by previous family-based studies, we hypothesize that aberrant rich club organization may be a trait marker for OCD. In the present study, 32 patients with OCD, 30 unaffected first-degree relatives (FDR) and 32 healthy controls (HC) underwent diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI). We examined the structural rich club organization and its interrelationship with functional coupling. Our results showed that rich club and peripheral connection strength in patients with OCD was lower than in HC, while it was intermediate in FDR. Finally, the coupling between structural and functional connections of the rich club, was decreased in FDR but not in OCD relative to HC, which suggests a buffering mechanism of brain functions in FDR. Overall, our findings suggest that alteration of the rich club organization may reflect a vulnerability biomarker for OCD, possibly buffered by structural and functional coupling of the rich club.}},\n  articleno    = {{102808}},\n  author       = {{Peng, Ziwen and Yang, Xinyi and Xu, Chuanyong and Wu, Xiangshu and Yang, Qiong and Wei, Zhen and Zhou, Zihan and Verguts, Tom and Chen, Qi}},\n  issn         = {{2213-1582}},\n  journal      = {{NEUROIMAGE-CLINICAL}},\n  keywords     = {{Obsessive-compulsive disorder,Vulnerability,Rich club organization,Peripheral connections,Diffusion tensor imaging}},\n  language     = {{eng}},\n  pages        = {{9}},\n  title        = {{Aberrant rich club organization in patients with obsessive-compulsive disorder and their unaffected first-degree relatives}},\n  url          = {{http://doi.org/10.1016/j.nicl.2021.102808}},\n  volume       = {{32}},\n  year         = {{2021}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Neural synchrony for adaptive control.\n \n \n \n \n\n\n \n Verbeke, Pieter; and Verguts, T.\n\n\n \n\n\n\n JOURNAL OF COGNITIVE NEUROSCIENCE, 33(11): 2394–2412. 2021.\n \n\n\n\n
\n\n\n\n \n \n $\"Neural$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8727659,\n  abstract     = {{Cognitive control can be adaptive along several dimensions, including intensity (how intensely do control signals influence bottom-up processing) and selectivity (what information is selected for further processing). Furthermore, control can be exerted along slow or fast time scales. Whereas control on a slow time scale is used to proactively prepare for upcoming challenges, control can also be used on a faster time scale to react to unexpected events that require control. Importantly, a systematic comparison of these dimensions and time scales remains lacking. Moreover, most current models of adaptive control allow predictions only at a behavioral, not neurophysiological, level, thus seriously reducing the range of available empirical restrictions for informing model formulation. The current article addresses this issue by implementing a control loop in an earlier model of neural synchrony. The resulting model is tested on a Stroop task. We observe that only the model that exerts cognitive control on intensity and selectivity dimensions, as well as on two time scales, can account for relevant behavioral and neurophysiological data. Our findings hold important implications for both cognitive control and how computational models can be empirically constrained.}},\n  author       = {{Verbeke, Pieter and Verguts, Tom}},\n  issn         = {{0898-929X}},\n  journal      = {{JOURNAL OF COGNITIVE NEUROSCIENCE}},\n  keywords     = {{ANTERIOR CINGULATE CORTEX,THETA DYNAMICS REVEAL,COGNITIVE CONTROL,CONFLICT ADAPTATION,FRONTAL THETA,OSCILLATORY DYNAMICS,INTEGRATIVE THEORY,COMMUNICATION,ATTENTION,MODEL}},\n  language     = {{eng}},\n  number       = {{11}},\n  pages        = {{2394--2412}},\n  title        = {{Neural synchrony for adaptive control}},\n  url          = {{http://doi.org/10.1162/jocn_a_01766}},\n  volume       = {{33}},\n  year         = {{2021}},\n}\n\n

\n

\n\n\n\n\n\n

\n

\n \n 2020\n \n \n (5)\n \n \n

\n

\n \n \n

\n \n\n \n \n \n \n \n \n Reward prediction error and declarative memory.\n \n \n \n \n\n\n \n Ergo, Kate; De Loof, E.; and Verguts, T.\n\n\n \n\n\n\n TRENDS IN COGNITIVE SCIENCES, 24(5): 388–397. 2020.\n \n\n\n\n
\n\n\n\n \n \n $\"Reward$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8659660,\n  abstract     = {{Learning based on reward prediction error (RPE) was originally proposed in the context of nondeclarative memory. We postulate that RPE may support declarative memory as well. Indeed, recent years have witnessed a number of independent empirical studies reporting effects of RPE on declarative memory. We provide a brief overview of these studies, identify emerging patterns, and discuss open issues such as the role of signed versus unsigned RPEs in declarative learning.}},\n  author       = {{Ergo, Kate and De Loof, Esther and Verguts, Tom}},\n  issn         = {{1364-6613}},\n  journal      = {{TRENDS IN COGNITIVE SCIENCES}},\n  keywords     = {{Experimental and Cognitive Psychology,Cognitive Neuroscience,Neuropsychology and Physiological Psychology,EPISODIC MEMORY,THETA OSCILLATIONS,DOPAMINE NEURONS,PEOPLES HYPERCORRECTION,HIGH-CONFIDENCE,HIPPOCAMPUS,RECONSOLIDATION,INFORMATION,ACTIVATION,RESPONSES}},\n  language     = {{eng}},\n  number       = {{5}},\n  pages        = {{388--397}},\n  title        = {{Reward prediction error and declarative memory}},\n  url          = {{http://doi.org/10.1016/j.tics.2020.02.009}},\n  volume       = {{24}},\n  year         = {{2020}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Cognitive effort modulates connectivity between dorsal anterior cingulate cortex and task-relevant cortical areas.\n \n \n \n \n\n\n \n Aben, Bart; Buc Calderon, C.; Van den Bussche, E.; and Verguts, T.\n\n\n \n\n\n\n JOURNAL OF NEUROSCIENCE, 40(19): 3838–3848. 2020.\n \n\n\n\n
\n\n\n\n \n \n $\"Cognitive$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8660202,\n  abstract     = {{Investment of cognitive effort is required in everyday life and has received ample attention in recent neurocognitive frameworks. The neural mechanism of effort investment is thought to be structured hierarchically, with dorsal anterior cingulate cortex (dACC) at the highest level, recruiting task-specific upstream areas. In the current fMRI study, we tested whether dACC is generally active when effort demand is high across tasks with different stimuli, and whether connectivity between dACC and task-specific areas is increased depending on the task requirements and effort level at hand. For that purpose, a perceptual detection task was administered that required male and female human participants to detect either a face or a house in a noisy image. Effort demand was manipulated by adding little (low effort) or much (high effort) noise to the images. Results showed a network of dACC, anterior insula (AI), and intraparietal sulcus (IPS) to be more active when effort demand was high, independent of the performed task (face or house detection). Importantly, effort demand modulated functional connectivity between dACC and face-responsive or house-responsive perceptual areas, depending on the task at hand. This shows that dACC, AI, and IPS constitute a general effort-responsive network and suggests that the neural implementation of cognitive effort involves dACC-initiated sensitization of task-relevant areas.}},\n  author       = {{Aben, Bart and Buc Calderon, Cristian and Van den Bussche, Eva and Verguts, Tom}},\n  issn         = {{0270-6474}},\n  journal      = {{JOURNAL OF NEUROSCIENCE}},\n  keywords     = {{General Neuroscience,anterior cingulate cortex,cognitive effort,fMRI,functional connectivity,PPI,MEDIAL FRONTAL-CORTEX,TOP-DOWN,DECISION-MAKING,INTEGRATIVE THEORY,VALUATION,FACE,MECHANISMS,ATTENTION,BEHAVIOR,SYSTEM}},\n  language     = {{eng}},\n  number       = {{19}},\n  pages        = {{3838--3848}},\n  title        = {{Cognitive effort modulates connectivity between dorsal anterior cingulate cortex and task-relevant cortical areas}},\n  url          = {{http://doi.org/10.1523/jneurosci.2948-19.2020}},\n  volume       = {{40}},\n  year         = {{2020}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n The hand-lateralization of spatial associations in working memory and long-term memory.\n \n \n \n \n\n\n \n Zhou, Dandan; Luo, J.; Yi, Z.; Li, Y.; Yang, S.; Verguts, T.; and Chen, Q.\n\n\n \n\n\n\n QUARTERLY JOURNAL OF EXPERIMENTAL PSYCHOLOGY, 73(8): 1150–1161. 2020.\n \n\n\n\n
\n\n\n\n \n \n $\"The$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8670423,\n  abstract     = {{Spatial-numerical and spatial-positional associations have been well documented in the domains of numerical cognition and working memory, respectively. However, such associations are typically calculated by directly comparing (e.g., subtracting) left- versus right-hand responses; it remains an open question whether such associations reside in each hand individually, or are exclusively localised in one of the two hands. We conducted six experiments to investigate the hand-lateralization of both spatial-numerical and spatial-positional associations. All experiments revealed that the spatial associations stemmed from left-hand responses, irrespective of the handedness of the subjects, but with the exception of the magnitude comparison task (Experiments 5 and 6). We propose that the hemispheric lateralization of the tasks in combination with the task-relevance of spatial associations can explain this pattern. More generally, we suggest that the contributions of left and right hands require more attention in spatial-numerical and spatial-positional research.}},\n  author       = {{Zhou, Dandan and Luo, Jie and Yi, Zizhen and Li, Yun and Yang, Shuting and Verguts, Tom and Chen, Qi}},\n  issn         = {{1747-0218}},\n  journal      = {{QUARTERLY JOURNAL OF EXPERIMENTAL PSYCHOLOGY}},\n  keywords     = {{Experimental and Cognitive Psychology,Physiology (medical),Physiology,General Psychology,Neuropsychology and Physiological Psychology,General Medicine,Hand-lateralization,SNARC effect,ordinal position effect,visuo-spatial coding,verbal-spatial coding,RESPONSE CODES SNARC,POLARITY CORRESPONDENCE,HEMISPHERIC-SPECIALIZATION,NUMERICAL ASSOCIATION,MENTAL REPRESENTATION,PERCEIVING NUMBERS,FUNCTIONAL LOCUS,SPACE,MARKEDNESS,MAGNITUDE}},\n  language     = {{eng}},\n  number       = {{8}},\n  pages        = {{1150--1161}},\n  title        = {{The hand-lateralization of spatial associations in working memory and long-term memory}},\n  url          = {{http://doi.org/10.1177/1747021819899533}},\n  volume       = {{73}},\n  year         = {{2020}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Variability in the analysis of a single neuroimaging dataset by many teams.\n \n \n \n \n\n\n \n Botvinik-Nezer, Rotem; Holzmeister, F.; Camerer, C. F.; Dreber, A.; Huber, J.; Johannesson, M.; Kirchler, M.; Iwanir, R.; Mumford, J. A.; Adcock, R. A.; Avesani, P.; Baczkowski, B. M.; Bajracharya, A.; Bakst, L.; Ball, S.; Barilari, M.; Bault, N.; Beaton, D.; Beitner, J.; Benoit, R. G.; Berkers, R. M. W. J.; Bhanji, J. P.; Biswal, B. B.; Bobadilla-Suarez, S.; Bortolini, T.; Bottenhorn, K. L.; Bowring, A.; Braem, S.; Brooks, H. R.; Brudner, E. G.; Buc Calderon, C.; Camilleri, J. A.; Castrellon, J. J.; Cecchetti, L.; Cieslik, E. C.; Cole, Z. J.; Collignon, O.; Cox, R. W.; Cunningham, W. A.; Czoschke, S.; Dadi, K.; Davis, C. P.; Luca, A. D.; Delgado, M. R.; Demetriou, L.; Dennison, J. B.; Di, X.; Dickie, E. W.; Dobryakova, E.; Donnat, C. L.; Dukart, J.; Duncan, N. W.; Durnez, J.; Eed, A.; Eickhoff, S. B.; Erhart, A.; Fontanesi, L.; Fricke, G. M.; Fu, S.; Galvan, A.; Gau, R.; Genon, S.; Glatard, T.; Glerean, E.; Goeman, J. J.; Golowin, S. A. E.; Gonzalez-Garcia, C.; Gorgolewski, K. J.; Grady, C. L.; Green, M. A.; Guassi Moreira, J. F.; Guest, O.; Hakimi, S.; Hamilton, J. P.; Hancock, R.; Handjaras, G.; Harry, B. B.; Hawco, C.; Herholz, P.; Herman, G.; Heunis, S.; Hoffstaedter, F.; Hogeveen, J.; Holmes, S.; Hu, C.; Huettel, S. A.; Hughes, M. E.; Iacovella, V.; Iordan, A. D.; Isager, P. M.; Isik, A. I.; Jahn, A.; Johnson, M. R.; Johnstone, T.; Joseph, M. J. E.; Juliano, A. C.; Kable, J. W.; Kassinopoulos, M.; Koba, C.; Kong, X.; Koscik, T. R.; Kucukboyaci, N. E.; Kuhl, B. A.; Kupek, S.; Laird, A. R.; Lamm, C.; Langner, R.; Lauharatanahirun, N.; Lee, H.; Lee, S.; Leemans, A.; Leo, A.; Lesage, E.; Li, F.; Li, M. Y. C.; Lim, P. C.; Lintz, E. N.; Liphardt, S. W.; Losecaat Vermeer, A. B.; Love, B. C.; Mack, M. L.; Malpica, N.; Marins, T.; Maumet, C.; McDonald, K.; McGuire, J. T.; Melero, H.; Mendez Leal, A. S.; Meyer, B.; Meyer, K. N.; Mihai, G.; Mitsis, G. D.; Moll, J.; Nielson, D. M.; Nilsonne, G.; Notter, M. P.; Olivetti, E.; Onicas, A. I.; Papale, P.; Patil, K. R.; Peelle, J. E.; Perez, A.; Pischedda, D.; Poline, J.; Prystauka, Y.; Ray, S.; Reuter-Lorenz, P. A.; Reynolds, R. C.; Ricciardi, E.; Rieck, J. R.; Rodriguez-Thompson, A. M.; Romyn, A.; Salo, T.; Samanez-Larkin, G. R.; Sanz-Morales, E.; Schlichting, M. L.; Schultz, D. H.; Shen, Q.; Sheridan, M. A.; Silvers, J. A.; Skagerlund, K.; Smith, A.; Smith, D. V.; Sokol-Hessner, P.; Steinkamp, S. R.; Tashjian, S. M.; Thirion, B.; Thorp, J. N.; Tinghog, G.; Tisdall, L.; Tompson, S. H.; Toro-Serey, C.; Torre Tresols, J. J.; Tozzi, L.; Truong, V.; Turella, L.; van 't Veer, A. E.; Verguts, T.; Vettel, J. M.; Vijayarajah, S.; Vo, K.; Wall, M. B.; Weeda, W. D.; Weis, S.; White, D. J.; Wisniewski, D.; Xifra-Porxas, A.; Yearling, E. A.; Yoon, S.; Yuan, R.; Yuen, K. S. L.; Zhang, L.; Zhang, X.; Zosky, J. E.; Nichols, T. E.; Poldrack, R. A.; and Schonberg, T.\n\n\n \n\n\n\n NATURE, 582(7810): 84–88. 2020.\n \n\n\n\n
\n\n\n\n \n \n $\"Variability$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8673623,\n abstract = {{Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses(1). The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset(2-5). Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed. The results obtained by seventy different teams analysing the same functional magnetic resonance imaging dataset show substantial variation, highlighting the influence of analytical choices and the importance of sharing workflows publicly and performing multiple analyses.}},\n author = {{Botvinik-Nezer, Rotem and Holzmeister, Felix and Camerer, Colin F. and Dreber, Anna and Huber, Juergen and Johannesson, Magnus and Kirchler, Michael and Iwanir, Roni and Mumford, Jeanette A. and Adcock, R. Alison and Avesani, Paolo and Baczkowski, Blazej M. and Bajracharya, Aahana and Bakst, Leah and Ball, Sheryl and Barilari, Marco and Bault, Nadege and Beaton, Derek and Beitner, Julia and Benoit, Roland G. and Berkers, Ruud M. W. J. and Bhanji, Jamil P. and Biswal, Bharat B. and Bobadilla-Suarez, Sebastian and Bortolini, Tiago and Bottenhorn, Katherine L. and Bowring, Alexander and Braem, Senne and Brooks, Hayley R. and Brudner, Emily G. and Buc Calderon, Cristian and Camilleri, Julia A. and Castrellon, Jaime J. and Cecchetti, Luca and Cieslik, Edna C. and Cole, Zachary J. and Collignon, Olivier and Cox, Robert W. and Cunningham, William A. and Czoschke, Stefan and Dadi, Kamalaker and Davis, Charles P. and Luca, Alberto De and Delgado, Mauricio R. and Demetriou, Lysia and Dennison, Jeffrey B. and Di, Xin and Dickie, Erin W. and Dobryakova, Ekaterina and Donnat, Claire L. and Dukart, Juergen and Duncan, Niall W. and Durnez, Joke and Eed, Amr and Eickhoff, Simon B. and Erhart, Andrew and Fontanesi, Laura and Fricke, G. Matthew and Fu, Shiguang and Galvan, Adriana and Gau, Remi and Genon, Sarah and Glatard, Tristan and Glerean, Enrico and Goeman, Jelle J. and Golowin, Sergej A. E. and Gonzalez-Garcia, Carlos and Gorgolewski, Krzysztof J. and Grady, Cheryl L. and Green, Mikella A. and Guassi Moreira, Joao F. and Guest, Olivia and Hakimi, Shabnam and Hamilton, J. Paul and Hancock, Roeland and Handjaras, Giacomo and Harry, Bronson B. and Hawco, Colin and Herholz, Peer and Herman, Gabrielle and Heunis, Stephan and Hoffstaedter, Felix and Hogeveen, Jeremy and Holmes, Susan and Hu, Chuan-Peng and Huettel, Scott A. and Hughes, Matthew E. and Iacovella, Vittorio and Iordan, Alexandru D. and Isager, Peder M. and Isik, Ayse I. and Jahn, Andrew and Johnson, Matthew R. and Johnstone, Tom and Joseph, Michael J. E. and Juliano, Anthony C. and Kable, Joseph W. and Kassinopoulos, Michalis and Koba, Cemal and Kong, Xiang-Zhen and Koscik, Timothy R. and Kucukboyaci, Nuri Erkut and Kuhl, Brice A. and Kupek, Sebastian and Laird, Angela R. and Lamm, Claus and Langner, Robert and Lauharatanahirun, Nina and Lee, Hongmi and Lee, Sangil and Leemans, Alexander and Leo, Andrea and Lesage, Elise and Li, Flora and Li, Monica Y. C. and Lim, Phui Cheng and Lintz, Evan N. and Liphardt, Schuyler W. and Losecaat Vermeer, Annabel B. and Love, Bradley C. and Mack, Michael L. and Malpica, Norberto and Marins, Theo and Maumet, Camille and McDonald, Kelsey and McGuire, Joseph T. and Melero, Helena and Mendez Leal, Adriana S. and Meyer, Benjamin and Meyer, Kristin N. and Mihai, Glad and Mitsis, Georgios D. and Moll, Jorge and Nielson, Dylan M. and Nilsonne, Gustav and Notter, Michael P. and Olivetti, Emanuele and Onicas, Adrian I. and Papale, Paolo and Patil, Kaustubh R. and Peelle, Jonathan E. and Perez, Alexandre and Pischedda, Doris and Poline, Jean-Baptiste and Prystauka, Yanina and Ray, Shruti and Reuter-Lorenz, Patricia A. and Reynolds, Richard C. and Ricciardi, Emiliano and Rieck, Jenny R. and Rodriguez-Thompson, Anais M. and Romyn, Anthony and Salo, Taylor and Samanez-Larkin, Gregory R. and Sanz-Morales, Emilio and Schlichting, Margaret L. and Schultz, Douglas H. and Shen, Qiang and Sheridan, Margaret A. and Silvers, Jennifer A. and Skagerlund, Kenny and Smith, Alec and Smith, David V. and Sokol-Hessner, Peter and Steinkamp, Simon R. and Tashjian, Sarah M. and Thirion, Bertrand and Thorp, John N. and Tinghog, Gustav and Tisdall, Loreen and Tompson, Steven H. and Toro-Serey, Claudio and Torre Tresols, Juan Jesus and Tozzi, Leonardo and Truong, Vuong and Turella, Luca and van 't Veer, Anna E. and Verguts, Tom and Vettel, Jean M. and Vijayarajah, Sagana and Vo, Khoi and Wall, Matthew B. and Weeda, Wouter D. and Weis, Susanne and White, David J. and Wisniewski, David and Xifra-Porxas, Alba and Yearling, Emily A. and Yoon, Sangsuk and Yuan, Rui and Yuen, Kenneth S. L. and Zhang, Lei and Zhang, Xu and Zosky, Joshua E. and Nichols, Thomas E. and Poldrack, Russell A. and Schonberg, Tom}},\n issn = {{0028-0836}},\n journal = {{NATURE}},\n keywords = {{PREDICTION MARKETS,NEURAL BASIS,REPLICABILITY}},\n language = {{eng}},\n number = {{7810}},\n pages = {{84--88}},\n title = {{Variability in the analysis of a single neuroimaging dataset by many teams}},\n url = {{http://doi.org/10.1038/s41586-020-2314-9}},\n volume = {{582}},\n year = {{2020}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Failure to modulate reward prediction errors in declarative learning with theta (6 Hz) frequency transcranial alternating current stimulation.\n \n \n \n \n\n\n \n Ergo, Kate; De Loof, E.; Debra, G.; Pastötter, B.; and Verguts, T.\n\n\n \n\n\n\n PLOS ONE, 15(12): 16. 2020.\n \n\n\n\n
\n\n\n\n \n \n $\"Failure$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8683745,\n  abstract     = {{Recent evidence suggests that reward prediction errors (RPEs) play an important role in declarative learning, but its neurophysiological mechanism remains unclear. Here, we tested the hypothesis that RPEs modulate declarative learning via theta-frequency oscillations, which have been related to memory encoding in prior work. For that purpose, we examined the interaction between RPE and transcranial Alternating Current Stimulation (tACS) in declarative learning. Using a between-subject (real versus sham stimulation group), single-blind stimulation design, 76 participants learned 60 Dutch-Swahili word pairs, while theta-frequency (6 Hz) tACS was administered over the medial frontal cortex (MFC). Previous studies have implicated MFC in memory encoding. We replicated our previous finding of signed RPEs (SRPEs) boosting declarative learning; with larger and more positive RPEs enhancing memory performance. However, tACS failed to modulate the SRPE effect in declarative learning and did not affect memory performance. Bayesian statistics supported evidence for an absence of effect. Our study confirms a role of RPE in declarative learning, but also calls for standardized procedures in transcranial electrical stimulation.}},\n  articleno    = {{e0237829}},\n  author       = {{Ergo, Kate and De Loof, Esther and Debra, Gillian and Pastötter, Bernhard and Verguts, Tom}},\n  issn         = {{1932-6203}},\n  journal      = {{PLOS ONE}},\n  keywords     = {{General Biochemistry,Genetics and Molecular Biology,General Agricultural and Biological Sciences,General Medicine,MEDIAL FRONTAL-CORTEX,WORKING-MEMORY,BRAIN-STIMULATION,EPISODIC MEMORY,PHASE SYNCHRONIZATION,ANTERIOR CINGULATE,GAMMA OSCILLATIONS,PREFRONTAL CORTEX,COMMON MECHANISM,ENTRAINMENT}},\n  language     = {{eng}},\n  number       = {{12}},\n  pages        = {{16}},\n  title        = {{Failure to modulate reward prediction errors in declarative learning with theta (6 Hz) frequency transcranial alternating current stimulation}},\n  url          = {{http://doi.org/10.1371/journal.pone.0237829}},\n  volume       = {{15}},\n  year         = {{2020}},\n}\n\n

\n

\n\n\n\n\n\n

\n

\n \n 2019\n \n \n (15)\n \n \n

\n

\n \n \n

\n \n\n \n \n \n \n \n \n Oscillatory signatures of reward prediction errors in declarative learning.\n \n \n \n \n\n\n \n Ergo, Kate; De Loof, E.; Janssens, C.; and Verguts, T.\n\n\n \n\n\n\n NEUROIMAGE, 186: 137–145. 2019.\n \n\n\n\n
\n\n\n\n \n \n $\"Oscillatory$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

\n

@article{8587408,\n  author       = {{Ergo, Kate and De Loof, Esther and Janssens, Clio and Verguts, Tom}},\n  issn         = {{1053-8119}},\n  journal      = {{NEUROIMAGE}},\n  keywords     = {{Cognitive Neuroscience,Neurology}},\n  language     = {{eng}},\n  pages        = {{137--145}},\n  publisher    = {{Elsevier BV}},\n  title        = {{Oscillatory signatures of reward prediction errors in declarative learning}},\n  url          = {{http://doi.org/10.1016/j.neuroimage.2018.10.083}},\n  volume       = {{186}},\n  year         = {{2019}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n The sound of beauty : how complexity determines aesthetic preference.\n \n \n \n \n\n\n \n Delplanque, Jeroen; De Loof, E.; Janssens, C.; and Verguts, T.\n\n\n \n\n\n\n ACTA PSYCHOLOGICA, 192: 146–152. 2019.\n \n\n\n\n
\n\n\n\n \n \n $\"The$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

\n

@article{8588050,\n  abstract     = {{Stimulus complexity is an important determinant of aesthetic preference. An influential idea is that increases instimulus complexity lead to increased preference up to an optimal point after which preference decreases (in-verted-U pattern). However, whereas some studies indeed observed this pattern, most studies instead showed anincreased preference for more complexity. One complicating issue is that it remains unclear how to definecomplexity. To address this, we approached complexity and its relation to aesthetic preference from a predictivecoding perspective. Here, low- and high-complexity stimuli would correspond to low and high levels of pre-diction errors, respectively. We expected participants to prefer stimuli which are neither too easy to predict (lowprediction error), nor too difficult (high prediction error). To test this, we presented two sequences of tones oneach trial that varied in predictability from highly regular (low prediction error) to completely random (highprediction error), and participants had to indicate which of the two sequences they preferred in a two-intervalforced-choice task. The complexity of each tone sequence (amount of prediction error) was estimated usingentropy. Results showed that participants tended to choose stimuli with intermediate complexity over those ofhigh or low complexity. This confirms the century-old idea that stimulus complexity has an inverted-U re-lationship to aesthetic preference.}},\n  author       = {{Delplanque, Jeroen and De Loof, Esther and Janssens, Clio and Verguts, Tom}},\n  issn         = {{0001-6918}},\n  journal      = {{ACTA PSYCHOLOGICA}},\n  keywords     = {{Experimental and Cognitive Psychology}},\n  language     = {{eng}},\n  pages        = {{146--152}},\n  publisher    = {{Elsevier BV}},\n  title        = {{The sound of beauty : how complexity determines aesthetic preference}},\n  url          = {{http://doi.org/10.1016/j.actpsy.2018.11.011}},\n  volume       = {{192}},\n  year         = {{2019}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n A post-decisional neural marker of confidence predicts information-seeking in decision-making.\n \n \n \n \n\n\n \n Desender, Kobe; Murphy, P.; Boldt, A.; Verguts, T.; and Yeung, N.\n\n\n \n\n\n\n JOURNAL OF NEUROSCIENCE, 39(17): 3309–3319. 2019.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8607851,\n  abstract     = {{Theoretical work predicts that decisions made with low confidence should lead to increased information-seeking. This is an adaptive strategy because it can increase the quality of a decision, and previous behavioral work has shown that decision-makers engage in such confidence-driven information-seeking. The present study aimed to characterize the neural markers that mediate the relationship between confidence and information-seeking. A paradigm was used in which 17 human participants (9 male) made an initial perceptual decision, and then decided whether or not they wanted to sample more evidence before committing to a final decision and confidence judgment. Predecisional and postdecisional event-related potential components were similarly modulated by the level of confidence and by information-seeking choices. Time-resolved multivariate decoding of scalp EEG signals first revealed that both information-seeking choices and decision confidence could be decoded from the time of the initial decision to the time of the subsequent information-seeking choice (within-condition decoding). Noabove-chance decoding was visible in the preresponse time window. Crucially, a classifier trained to decode high versus low confidence predicted information-seeking choices after the initial perceptual decision (across-condition decoding). This time window corresponds to that of a postdecisional neural marker of confidence. Collectively, our findings demonstrate, for the first time, that neural indices of confidence are functionally involved in information-seeking decisions.}},\n  author       = {{Desender, Kobe and Murphy, Peter and Boldt, Annika and Verguts, Tom and Yeung, Nick}},\n  issn         = {{0270-6474}},\n  journal      = {{JOURNAL OF NEUROSCIENCE}},\n  keywords     = {{General Neuroscience,confidence,decision-making,error positivity,information sampling,information-seeking,metacognition,SIGNAL-DETECTION,UNCERTAINTY,REPRESENTATIONS,DYNAMICS,ADVICE,CHOICE,P300,TIME}},\n  language     = {{eng}},\n  number       = {{17}},\n  pages        = {{3309--3319}},\n  title        = {{A post-decisional neural marker of confidence predicts information-seeking in decision-making}},\n  url          = {{http://doi.org/10.1523/JNEUROSCI.2620-18.2019}},\n  volume       = {{39}},\n  year         = {{2019}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n The graded fate of unattended stimulus representations in visuospatial working memory.\n \n \n \n \n\n\n \n Sahan, Muhammet Ikbal; Dalmaijer, E. S; Verguts, T.; Husain, M.; and Fias, W.\n\n\n \n\n\n\n FRONTIERS IN PSYCHOLOGY, 10: 13. 2019.\n \n\n\n\n
\n\n\n\n \n \n $\"The$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8608836,\n  abstract     = {{As in visual perception, information can be selected for prioritized processing at the expense of unattended representations in visual working memory (VWM). However, what is not clear is whether and how this prioritization degrades the unattended representations. We addressed two hypotheses. First, the representational quality of unattended items could be degraded as a function of the spatial distance to attended information in VWM. Second, the strength with which an item is bound to its location is degraded as a function of the spatial distance to attended information in VWM. To disentangle these possibilities, we designed an experiment in which participants performed a continuous production task in which they memorized a visual array with colored discs, one of which was spatially retro-cued, informing the target location of an impending probe that was to be recalled (Experiment 1). We systematically varied the spatial distance between the cued and probed locations and obtained model-based estimates of the representational quality and binding strengths at varying cue-probe distances. Although the representational quality of the unattended representations remained unaffected by the cue-probe distance, spatially graded binding strengths were observed, as reflected in more spatial confusions at smaller cue-probe distances. These graded binding strengths were further replicated with a model-free approach in a categorical version of the production task in which stimuli and responses consisted of easily discriminable colors (Experiment 2). These results demonstrate that unattended representations are prone to spatial confusions due to spatial degradation of binding strengths in WM, even though they are stored with the same representational quality.}},\n  articleno    = {{374}},\n  author       = {{Sahan, Muhammet Ikbal and Dalmaijer, Edwin S and Verguts, Tom and Husain, Masud and Fias, Wim}},\n  issn         = {{1664-1078}},\n  journal      = {{FRONTIERS IN PSYCHOLOGY}},\n  keywords     = {{SPATIAL-DISTRIBUTION,ATTENTION,SUPPRESSION,DETERMINES,RESOURCES,GRADIENTS,OBJECTS,FOCUS,spatial attention,working memory,memory quality,binding errors,distance effects}},\n  language     = {{eng}},\n  pages        = {{13}},\n  title        = {{The graded fate of unattended stimulus representations in visuospatial working memory}},\n  url          = {{http://doi.org/10.3389/fpsyg.2019.00374}},\n  volume       = {{10}},\n  year         = {{2019}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Context-dependent modulation of cognitive control involves different temporal profiles of fronto-parietal activity.\n \n \n \n \n\n\n \n Aben, Lambertus; Buc Calderon, C.; Van der Cruyssen, L.; Picksak, D.; Van den Bussche, E.; and Verguts, T.\n\n\n \n\n\n\n NEUROIMAGE, 189: 755–762. 2019.\n \n\n\n\n
\n\n\n\n \n \n $\"Context-dependent$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8609839,\n  abstract     = {{To efficiently deal with quickly changing task demands, we often need to organize our behaviour on different time scales. For example, to ignore irrelevant and select relevant information, cognitive control might be applied in reactive (short time scale) or proactive (long time scale) mode. These two control modes play a pivotal role in cognitive-neuroscientific theorizing but the temporal dissociation of the underlying neural mechanisms is not well established empirically. In this fMRI study, a cognitive control task was administered in contexts with mainly congruent (MC) and mainly incongruent (MI) trials to induce reactive and proactive control, respectively. Based on behavioural profiles, we expected cognitive control in the MC context to be characterized by transient activity (measured on-trial) in task-relevant areas. In the MI context, cognitive control was expected to be reflected in sustained activity (measured in the intertrial interval) in similar or different areas. Results show that in the MC context, on-trial transient activity (incongruent - congruent trials) was increased in fronto-parietal areas, compared to the MI context. These areas included dorsolateral prefrontal cortex (dlPFC) and intraparietal sulcus (IPS). In the MI context, sustained activity in similar fronto-parietal areas during the intertrial interval was increased, compared to the MC context. These results illuminate how context-dependent reactive and proactive control subtend the same brain areas but operate on different time scales.}},\n  author       = {{Aben, Lambertus and Buc Calderon, Cristian and Van der Cruyssen, Laurens and Picksak, Doerte and Van den Bussche, Eva and Verguts, Tom}},\n  issn         = {{1053-8119}},\n  journal      = {{NEUROIMAGE}},\n  keywords     = {{ANTERIOR CINGULATE CORTEX,PREFRONTAL CORTEX,INTEGRATIVE THEORY,CONTROL NETWORK,TASK-SET,CONFLICT,MECHANISMS,INTERFERENCE,REGIONS,ADJUSTMENTS,Attention,Cognitive effort,fMRI,Proportion congruency,Proactive,control,Reactive control}},\n  language     = {{eng}},\n  pages        = {{755--762}},\n  publisher    = {{Academic Press Inc Elsevier Science}},\n  title        = {{Context-dependent modulation of cognitive control involves different temporal profiles of fronto-parietal activity}},\n  url          = {{http://doi.org/10.1016/j.neuroimage.2019.02.004}},\n  volume       = {{189}},\n  year         = {{2019}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Persistent modification of cognitive control through attention training.\n \n \n \n \n\n\n \n Aben, Lambertus; Iseni, B.; Van den Bussche, E.; and Verguts, T.\n\n\n \n\n\n\n QUARTERLY JOURNAL OF EXPERIMENTAL PSYCHOLOGY, 72(3): 413–423. 2019.\n \n\n\n\n
\n\n\n\n \n \n $\"Persistent$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8609840,\n  abstract     = {{An important aspect of cognitive control is to direct attention towards relevant information and away from distracting information. This attentional modulation is at the core of several influential frameworks, but its trainability and generalisability remain unclear. To address this issue, two groups of subjects were invited to the lab on three consecutive days. On Day 2, they performed an arrow priming task which trained them to adopt an attentional bias towards (prime-attended group) or away from (prime-diverted group) a potentially conflicting prime. Direct generalisation of the attention training was measured by assessing task performance on the same task without the attentional manipulation directly after training (Day 2) and the next day (Day 3), and comparing it to baseline (Day 1). Performance on this direct transfer task showed a difference in attentional modulation between groups directly after training that persisted the next day. No cross-task generalisation was found to two other tasks that were closely or more remotely related to the trained task. Together, these results are in accordance with cognitive control frameworks that limit attentional modulation to the specific features of the trained task.}},\n  author       = {{Aben, Lambertus and Iseni, Blerina and Van den Bussche, Eva and Verguts, Tom}},\n  issn         = {{1747-0218}},\n  journal      = {{QUARTERLY JOURNAL OF EXPERIMENTAL PSYCHOLOGY}},\n  keywords     = {{PROPORTION-CONGRUENT,CONFLICT ADAPTATION,APPROACH BIAS,MECHANISMS,PSYCHOLOGY,STIMULI,MODELS,NO,Attention,cognitive control,training,generalisation,conflict}},\n  language     = {{eng}},\n  number       = {{3}},\n  pages        = {{413--423}},\n  publisher    = {{Routledge Journals, Taylor & Francis Ltd}},\n  title        = {{Persistent modification of cognitive control through attention training}},\n  url          = {{http://doi.org/10.1177/1747021818757979}},\n  volume       = {{72}},\n  year         = {{2019}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Anticipation of a mentally effortful task recruits Dorsolateral Prefrontal Cortex : an fNIRS validation study.\n \n \n \n \n\n\n \n Vassena, Eliana; Gerrits, R.; Demanet, J.; Verguts, T.; and Siugzdaite, R.\n\n\n \n\n\n\n NEUROPSYCHOLOGIA, 123: 106–115. 2019.\n \n\n\n\n
\n\n\n\n \n \n $\"Anticipation$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{8610870,\n  author       = {{Vassena, Eliana and Gerrits, Robin and Demanet, Jelle and Verguts, Tom and Siugzdaite, Roma}},\n  issn         = {{0028-3932}},\n  journal      = {{NEUROPSYCHOLOGIA}},\n  language     = {{eng}},\n  pages        = {{106--115}},\n  publisher    = {{Elsevier}},\n  title        = {{Anticipation of a mentally effortful task recruits Dorsolateral Prefrontal Cortex : an fNIRS validation study}},\n  url          = {{http://doi.org/10.1016/j.neuropsychologia.2018.04.033}},\n  volume       = {{123}},\n  year         = {{2019}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n The neural mechanism of number line bisection : a fMRI study.\n \n \n \n \n\n\n \n Liu, Dixiu; Zhou, D.; Li, M.; Li, M.; Dong, W.; Verguts, T.; and Chen, Q.\n\n\n \n\n\n\n NEUROPSYCHOLOGIA, 129: 37–46. 2019.\n \n\n\n\n
\n\n\n\n \n \n $\"The$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8610873,\n  abstract     = {{The neural networks involved in number line bisection are poorly understood. We used functional magnetic resonance imaging (fMRI) to investigate these. fMRI was analyzed from 28 healthy volunteers who performed number and physical line bisection tasks (and their respective baselines). Whole brain analyses showed that these two bisection tasks shared common neural correlates in bilateral parietal-frontal networks; furthermore, bilateral parietal-frontal areas, right cerebellum, left insula and supplementary motor area (SMA) showed higher activity when contrasting the number line with a physical line bisection task. Importantly, psychophysiological interaction (PPI) analyses further indicated that left SMA and right cerebellum were connected to parietal-frontal areas for implementing the number line bisection task. Our findings suggested that a visuospatial attention control system was recruited, and mental imagery of a number line was used to find the midpoint of a numerical interval without calculations.}},\n  author       = {{Liu, Dixiu and Zhou, Dandan and Li, Mengjin and Li, Min and Dong, Wenshan and Verguts, Tom and Chen, Qi}},\n  issn         = {{0028-3932}},\n  journal      = {{NEUROPSYCHOLOGIA}},\n  keywords     = {{Experimental and Cognitive Psychology,Cognitive Neuroscience,Behavioral Neuroscience,SUPPLEMENTARY MOTOR AREA,SPATIAL ATTENTION,SPACE,CEREBELLUM,REPRESENTATION,NEGLECT,ADAPTATION,DISTINCT,CORTEX,PRESUPPLEMENTARY,Number and space,Number line bisection,Parietal-frontal network}},\n  language     = {{eng}},\n  pages        = {{37--46}},\n  title        = {{The neural mechanism of number line bisection : a fMRI study}},\n  url          = {{http://doi.org/10.1016/j.neuropsychologia.2019.03.007}},\n  volume       = {{129}},\n  year         = {{2019}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n The metaphoric nature of the ordinal position effect.\n \n \n \n \n\n\n \n Zhou, Dandan; Zhong, H.; Dong, W.; Li, M.; Verguts, T.; and Chen, Q.\n\n\n \n\n\n\n QUARTERLY JOURNAL OF EXPERIMENTAL PSYCHOLOGY, 72(8): 2121–2129. 2019.\n \n\n\n\n
\n\n\n\n \n \n $\"The$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8623916,\n  abstract     = {{Serial orders are thought to be spatially represented in working memory: The beginning items in the memorised sequence are associated with the left side of space and the ending items are associated with the right side of space. However, the origin of this ordinal position effect has remained unclear. It was suggested that the direction of serial order–space interaction is related to the reading/writing experience. An alternative hypothesis is that it originates from the “more is right”/“more is up” spatial metaphors we use in daily life. We can adjudicate between the two viewpoints in Chinese readers; they read left-to-right but also have a culturally ancient top-to-bottom reading/writing direction. Thus, the reading/writing viewpoint predicts no or a top-to-bottom effect in serial order–space interaction; whereas the spatial metaphor theory predicts a clear bottom-to-top effect. We designed four experiments to investigate this issue. First, we found a left-to-right ordinal position effect, replicating results obtained in Western populations. However, the vertical ordinal position effect was in the bottom-to-top direction; moreover, it was modulated by hand position (e.g., left hand bottom or up). We suggest that order–space interactions may originate from different sources and are driven by metaphoric comprehension, which itself may ground cognitive processing.}},\n  author       = {{Zhou, Dandan and Zhong, Hanxi and Dong, Wenshan and Li, Min and Verguts, Tom and Chen, Qi}},\n  issn         = {{1747-0218}},\n  journal      = {{QUARTERLY JOURNAL OF EXPERIMENTAL PSYCHOLOGY}},\n  keywords     = {{Experimental and Cognitive Psychology,Physiology (medical),Physiology,General Psychology,Neuropsychology and Physiological Psychology,General Medicine,WORKING-MEMORY,NUMBER LINE,SPATIALISATION,REPRESENTATION,INFORMATION,RESPONSES,REVERSE,Working memory,ordinal position effect,SPoARC effect,metaphor}},\n  language     = {{eng}},\n  number       = {{8}},\n  pages        = {{2121--2129}},\n  title        = {{The metaphoric nature of the ordinal position effect}},\n  url          = {{http://doi.org/10.1177/1747021819832860}},\n  volume       = {{72}},\n  year         = {{2019}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Preparing for hard times : scalp and intracranial physiological signatures of proactive cognitive control.\n \n \n \n \n\n\n \n De Loof, Esther; Vassena, E.; Janssens, C.; De Taeye, L.; Meurs, A.; Van Roost, D.; Boon, P.; Raedt, R.; and Verguts, T.\n\n\n \n\n\n\n PSYCHOPHYSIOLOGY, 56(10): 14. 2019.\n \n\n\n\n
\n\n\n\n \n \n $\"Preparing$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8624466,\n  abstract     = {{Based on reward and difficulty information, people can strategically adjust proactive cognitive control. fMRI research shows that motivated proactive control is implemented through fronto‐parietal control networks that are triggered by reward and difficulty cues. Here, we investigate electrophysiological signatures of proactive control. Previously, the contingent negative variation (CNV) in the ERPs and oscillatory power in the theta (4–8 Hz) and alpha band (8–14 Hz) have been suggested as signatures of control implementation. However, experimental designs did not always separate control implementation from motor preparation. Critically, we used a mental calculation task to investigate effects of proactive control implementation on the CNV and on theta and alpha power, in absence of motor preparation. In the period leading up to task onset, we found a more negative CNV, increased theta power, and decreased alpha power for hard versus easy calculations, showing increased proactive control implementation when a difficult task was expected. These three measures also correlated with behavioral performance, both across trials and across subjects. In addition to scalp EEG in healthy participants, we collected intracranial local field potential recordings in an epilepsy patient. We observed a slow‐drift component that was more pronounced for hard trials in a hippocampal location, possibly reflecting task‐specific preparation for hard mental calculations. The current study thus shows that difficulty information triggers proactive control in absence of motor preparation and elucidates its neurophysiological signatures.}},\n  articleno    = {{e13417}},\n  author       = {{De Loof, Esther and Vassena, Eliana and Janssens, Clio and De Taeye, Leen and Meurs, Alfred and Van Roost, Dirk and Boon, Paul and Raedt, Robrecht and Verguts, Tom}},\n  issn         = {{0048-5772}},\n  journal      = {{PSYCHOPHYSIOLOGY}},\n  keywords     = {{alpha rhythm,attention,cognitive control,EEG,motivation,oscillation,time frequency analyses,CONTINGENT NEGATIVE-VARIATION,ANTERIOR CINGULATE CORTEX,DOPAMINERGIC MIDBRAIN,ATTENTIONAL CONTROL,ALPHA-OSCILLATIONS,NEURAL MECHANISMS,DECISION-MAKING,REWARD-PROSPECT,WORKING-MEMORY,THETA}},\n  language     = {{eng}},\n  number       = {{10}},\n  pages        = {{14}},\n  title        = {{Preparing for hard times : scalp and intracranial physiological signatures of proactive cognitive control}},\n  url          = {{http://doi.org/10.1111/psyp.13417}},\n  volume       = {{56}},\n  year         = {{2019}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Confidence predicts speed-accuracy tradeoff for subsequent decisions.\n \n \n \n \n\n\n \n Desender, Kobe; Boldt, A.; Verguts, T.; and Donner, T. H\n\n\n \n\n\n\n ELIFE, 8. 2019.\n \n\n\n\n
\n\n\n\n \n \n $\"Confidence$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8626341,\n  abstract     = {{When external feedback about decision outcomes is lacking, agents need to adapt their decision policies based on an internal estimate of the correctness of their choices (i.e., decision confidence). We hypothesized that agents use confidence to continuously update the tradeoff between the speed and accuracy of their decisions: When confidence is low in one decision, the agent needs more evidence before committing to a choice in the next decision, leading to slower but more accurate decisions. We tested this hypothesis by fitting a bounded accumulation decision model to behavioral data from three different perceptual choice tasks. Decision bounds indeed depended on the reported confidence on the previous trial, independent of objective accuracy. This increase in decision bound was predicted by a centro-parietal EEG component sensitive to confidence. We conclude that internally computed neural signals of confidence predict the ongoing adjustment of decision policies.</jats:p>}},\n  articleno    = {{e43499}},\n  author       = {{Desender, Kobe and Boldt, Annika and Verguts, Tom and Donner, Tobias H}},\n  issn         = {{2050-084X}},\n  journal      = {{ELIFE}},\n  keywords     = {{General Biochemistry,Genetics and Molecular Biology,General Immunology and Microbiology,General Neuroscience,General Medicine,ERROR-DETECTION,COGNITIVE CONTROL,NEURAL BASIS,CHOICE,TIME,THETA,COMPUTATION,INTEGRATION,MECHANISMS,CERTAINTY}},\n  language     = {{eng}},\n  title        = {{Confidence predicts speed-accuracy tradeoff for subsequent decisions}},\n  url          = {{http://doi.org/10.7554/elife.43499}},\n  volume       = {{8}},\n  year         = {{2019}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Learning to synchronize : how biological agents can couple neural task modules for dealing with the stability-plasticity dilemma.\n \n \n \n \n\n\n \n Verbeke, Pieter; and Verguts, T.\n\n\n \n\n\n\n PLOS COMPUTATIONAL BIOLOGY, 15(8): 25. 2019.\n \n\n\n\n
\n\n\n\n \n \n $\"Learning$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8626658,\n  abstract     = {{We provide a novel computational framework on how biological and artificial agents can learn to flexibly couple and decouple neural task modules for cognitive processing. In this way, they can address the stability-plasticity dilemma. For this purpose, we combine two prominent computational neuroscience principles, namely Binding by Synchrony and Reinforcement Learning. The model learns to synchronize task-relevant modules, while also learning to desynchronize currently task-irrelevant modules. As a result, old (but currently task-irrelevant) information is protected from overwriting (stability) while new information can be learned quickly in currently task-relevant modules (plasticity). We combine learning to synchronize with task modules that learn via one of several classical learning algorithms (Rescorla-Wagner, backpropagation, Boltzmann machines). The resulting combined model is tested on a reversal learning paradigm where it must learn to switch between three different task rules. We demonstrate that our combined model has significant computational advantages over the original network without synchrony, in terms of both stability and plasticity. Importantly, the resulting models' processing dynamics are also consistent with empirical data and provide empirically testable hypotheses for future MEG/EEG studies.}},\n  articleno    = {{e1006604}},\n  author       = {{Verbeke, Pieter and Verguts, Tom}},\n  issn         = {{1553-7358}},\n  journal      = {{PLOS COMPUTATIONAL BIOLOGY}},\n  keywords     = {{ANTERIOR CINGULATE CORTEX,PREFRONTAL CORTEX,INTEGRATIVE THEORY,COMPUTATIONAL MODEL,DECISION-MAKING,FRONTAL THETA,SYSTEMS,COMMUNICATION,OSCILLATIONS,ACCOUNT}},\n  language     = {{eng}},\n  number       = {{8}},\n  pages        = {{25}},\n  title        = {{Learning to synchronize : how biological agents can couple neural task modules for dealing with the stability-plasticity dilemma}},\n  url          = {{http://doi.org/10.1371/journal.pcbi.1006604}},\n  volume       = {{15}},\n  year         = {{2019}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Striatal dopamine D2 binding correlates with locus of control : preliminary evidence from [11C]raclopride Positron Emission Tomography.\n \n \n \n \n\n\n \n Vassena, Eliana; Van Opstal, F.; Goethals, I.; and Verguts, T.\n\n\n \n\n\n\n INTERNATIONAL JOURNAL OF PSYCHOPHYSIOLOGY, 146: 117–124. 2019.\n \n\n\n\n
\n\n\n\n \n \n $\"Striatal$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8634084,\n  abstract     = {{The ability to exert control has been widely investigated as a hallmark of adaptive behaviour. Dopamine is recognized as the key neuromodulator mediating various control-related processes. The neural mechanisms underlying the subjective perception of being in control, or Locus of Control (LOC) are however less clear. LOC indicates the subjective tendency to attribute environmental outcomes to one's actions (internal LOC) or instead to external incontrollable factors (external LOC). Here we hypothesized that dopamine levels also relate to LOC. Previous work shows that dopamine signaling mediates learning of action-outcome relationships, outcome predictability, and opportunity cost. Prominent theories propose dopamine dysregulation as the key pathogenetic mechanism in schizophrenia and depression. Critically, external LOC is a risk factor for schizophrenia and depression, and predicts increased vulnerability to stress. However, a direct link between LOC and dopamine levels in healthy control had not been demonstrated. The purpose of our study was to investigate this link. Using [11C]raclopride Positron Emission Tomography we tested the relationship between D2 receptor binding in the striatum and LOC (measured with the Rotter Locus of Control scale) in 15 healthy volunteers. Our results show a large and positive correlation: increased striatal D2 binding was associated with External LOC. This finding opens promising avenues for the study of several psychological impairments that have been associated with both dopamine and LOC, such as addiction, schizophrenia, and depression.}},\n  author       = {{Vassena, Eliana and Van Opstal, Filip and Goethals, Ingeborg and Verguts, Tom}},\n  issn         = {{0167-8760}},\n  journal      = {{INTERNATIONAL JOURNAL OF PSYCHOPHYSIOLOGY}},\n  keywords     = {{Locus of control,Dopamine,D2 binding,Attribution,PET,REFERENCE TISSUE MODEL,INDIVIDUAL-DIFFERENCES,COMPUTATIONAL MODELS,SYNTHESIS CAPACITY,PREFRONTAL CORTEX,DECISION-MAKING,SEX-DIFFERENCES,REWARD,STRESS,SCHIZOPHRENIA}},\n  language     = {{eng}},\n  pages        = {{117--124}},\n  title        = {{Striatal dopamine D2 binding correlates with locus of control : preliminary evidence from [11C]raclopride Positron Emission Tomography}},\n  url          = {{http://doi.org/10.1016/j.ijpsycho.2019.09.016}},\n  volume       = {{146}},\n  year         = {{2019}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Attentional orienting relies on Bayesian estimates of expected and unexpected uncertainty.\n \n \n \n \n\n\n \n Marzecova, Anna; Van den Bussche, E.; and Verguts, T.\n\n\n \n\n\n\n In pages 1–4, 2019. \n \n\n\n\n
\n\n\n\n \n \n $\"Attentional$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@inproceedings{8634375,\n  author       = {{Marzecova, Anna and Van den Bussche, Eva and Verguts, Tom}},\n  keywords     = {{attention,Bayesian,neuromodulation,pupil dilation,uncertainty}},\n  language     = {{eng}},\n  location     = {{Berlin}},\n  pages        = {{1--4}},\n  title        = {{Attentional orienting relies on Bayesian estimates of expected and unexpected uncertainty}},\n  url          = {{http://doi.org/10.32470/CCN.2019.1203-0}},\n  year         = {{2019}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Variability in the analysis of a single neuroimaging dataset by many teams.\n \n \n \n \n\n\n \n Botvinik-Nezer, Rotem; Holzmeister, F.; Camerer, C. F.; Dreber, A.; Huber, J.; Johannesson, M.; Kirchler, M.; Iwanir, R.; Mumford, J. A.; Adcock, A.; Avesani, P.; Baczkowski, B.; Bajracharya, A.; Bakst, L.; Ball, S.; Barilari, M.; Bault, N.; Beaton, D.; Beitner, J.; Benoit, R.; Berkers, R.; Bhanji, J.; Biswal, B.; Bobadilla-Suarez, S.; Bortolini, T.; Bottenhorn, K.; Bowring, A.; Braem, S.; Brooks, H.; Brudner, E.; Buc Calderon, C.; Camilleri, J.; Castrellon, J.; Cecchetti, L.; Cieslik, E.; Cole, Z.; Collignon, O.; Cox, R.; Cunningham, W.; Czoschke, S.; Dadi, K.; Davis, C.; De Luca, A.; Delgado, M.; Demetriou, L.; Dennison, J.; Di, X.; Dickie, E.; Dobryakova, E.; Donnat, C.; Dukart, J.; Duncan, N. W.; Durnez, J.; Eed, A.; Eickhoff, S.; Erhart, A.; Fontanesi, L.; Fricke, G. M.; Galvan, A.; Gau, R.; Genon, S.; Glatard, T.; Glerean, E.; Goeman, J.; Golowin, S.; Gonzalez-Garcia, C.; Gorgolewski, K.; Grady, C.; Green, M.; Guassi Moreira, J.; Guest, O.; Hakimi, S.; Hamilton, J. P.; Hancock, R.; Handjaras, G.; Harry, B.; Hawco, C.; Herholz, P.; Herman, G.; Heunis, S.; Hoffstaedter, F.; Hogeveen, J.; Holmes, S.; Hu, C.; Huettel, S.; Hughes, M.; Iacovella, V.; Iordan, A.; Isager, P.; Isik, A. I.; Jahn, A.; Johnson, M.; Johnstone, T.; Joseph, M.; Juliano, A.; Kable, J.; Kassinopoulos, M.; Koba, C.; Kong, X.; Koscik, T.; Kucukboyaci, N. E.; Kuhl, B.; Kupek, S.; Laird, A.; Lamm, C.; Langner, R.; Lauharatanahirun, N.; Lee, H.; Lee, S.; Leemans, A.; Leo, A.; Lesage, E.; Li, F.; Li, M.; Lim, P. C.; Lintz, E.; Liphardt, S.; Losecaat Vermeer, A.; Love, B.; Mack, M.; Malpica, N.; Marins, T.; Maumet, C.; McDonald, K.; McGuire, J.; Melero, H.; Méndez Leal, A.; Meyer, B.; Meyer, K.; Mihai, P.; Mitsis, G.; Moll, J.; Nielson, D.; Nilsonne, G.; Notter, M.; Olivetti, E.; Onicas, A.; Papale, P.; Patil, K.; Peelle, J. E.; Pérez, A.; Pischedda, D.; Poline, J.; Prystauka, Y.; Ray, S.; Reuter-Lorenz, P.; Reynolds, R.; Ricciardi, E.; Rieck, J.; Rodriguez-Thompson, A.; Romyn, A.; Salo, T.; Samanez-Larkin, G.; Sanz-Morales, E.; Schlichting, M.; Schultz, D.; Shen, Q.; Sheridan, M.; Shiguang, F.; Silvers, J.; Skagerlund, K.; Smith, A.; Smith, D.; Sokol-Hessner, P.; Steinkamp, S.; Tashjian, S.; Thirion, B.; Thorp, J.; Tinghög, G.; Tisdall, L.; Tompson, S.; Toro-Serey, C.; Torre, J.; Tozzi, L.; Truong, V.; Turella, L.; van’t Veer, A. E.; Verguts, T.; Vettel, J.; Vijayarajah, S.; Vo, K.; Wall, M.; Weeda, W. D.; Weis, S.; White, D.; Wisniewski, D.; Xifra-Porxas, A.; Yearling, E.; Yoon, S.; Yuan, R.; Yuen, K.; Zhang, L.; Zhang, X.; Zosky, J.; Nichols, T. E.; Poldrack, R. A.; and Schonberg, T.\n\n\n \n\n\n\n 2019.\n \n\n\n\n
\n\n\n\n \n \n $\"Variability$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@misc{8641719,\n  abstract     = {{Data analysis workflows in many scientific domains have become increasingly complex and flexible. To assess the impact of this flexibility on functional magnetic resonance imaging (fMRI) results, the same dataset was independently analyzed by 70 teams, testing nine ex-ante hypotheses. The flexibility of analytic approaches is exemplified by the fact that no two teams chose identical workflows to analyze the data. This flexibility resulted in sizeable variation in hypothesis test results, even for teams whose statistical maps were highly correlated at intermediate stages of their analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Importantly, meta-analytic approaches that aggregated information across teams yielded significant consensus in activated regions across teams. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset. Our findings show that analytic flexibility can have substantial effects on scientific conclusions, and demonstrate factors related to variability in fMRI. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for multiple analyses of the same data. Potential approaches to mitigate issues related to analytical variability are discussed.}},\n  author       = {{Botvinik-Nezer, Rotem and Holzmeister, Felix and Camerer, Colin F. and Dreber, Anna and Huber, Juergen and Johannesson, Magnus and Kirchler, Michael and Iwanir, Roni and Mumford, Jeanette A. and Adcock, Alison and Avesani, Paolo and Baczkowski, Blazej and Bajracharya, Aahana and Bakst, Leah and Ball, Sheryl and Barilari, Marco and Bault, Nadège and Beaton, Derek and Beitner, Julia and Benoit, Roland and Berkers, Ruud and Bhanji, Jamil and Biswal, Bharat and Bobadilla-Suarez, Sebastian and Bortolini, Tiago and Bottenhorn, Katherine and Bowring, Alexander and Braem, Senne and Brooks, Hayley and Brudner, Emily and Buc Calderon, Cristian and Camilleri, Julia and Castrellon, Jaime and Cecchetti, Luca and Cieslik, Edna and Cole, Zachary and Collignon, Olivier and Cox, Robert and Cunningham, William and Czoschke, Stefan and Dadi, Kamalaker and Davis, Charles and De Luca, Alberto and Delgado, Mauricio and Demetriou, Lysia and Dennison, Jeffrey and Di, Xin and Dickie, Erin and Dobryakova, Ekaterina and Donnat, Claire and Dukart, Juergen and Duncan, Niall W. and Durnez, Joke and Eed, Amr and Eickhoff, Simon and Erhart, Andrew and Fontanesi, Laura and Fricke, G. Matthew and Galvan, Adriana and Gau, Remi and Genon, Sarah and Glatard, Tristan and Glerean, Enrico and Goeman, Jelle and Golowin, Sergej and Gonzalez-Garcia, Carlos and Gorgolewski, Krzysztof and Grady, Cheryl and Green, Mikella and Guassi Moreira, João and Guest, Olivia and Hakimi, Shabnam and Hamilton, J. Paul and Hancock, Roeland and Handjaras, Giacomo and Harry, Bronson and Hawco, Colin and Herholz, Peer and Herman, Gabrielle and Heunis, Stephan and Hoffstaedter, Felix and Hogeveen, Jeremy and Holmes, Susan and Hu, Chuan-Peng and Huettel, Scott and Hughes, Matthew and Iacovella, Vittorio and Iordan, Alexandru and Isager, Peder and Isik, Ayse Ilkay and Jahn, Andrew and Johnson, Matthew and Johnstone, Tom and Joseph, Michael and Juliano, Anthony and Kable, Joseph and Kassinopoulos, Michalis and Koba, Cemal and Kong, Xiang-Zhen and Koscik, Timothy and Kucukboyaci, Nuri Erkut and Kuhl, Brice and Kupek, Sebastian and Laird, Angela and Lamm, Claus and Langner, Robert and Lauharatanahirun, Nina and Lee, Hongmi and Lee, Sangil and Leemans, Alexander and Leo, Andrea and Lesage, Elise and Li, Flora and Li, Monica and Lim, Phui Cheng and Lintz, Evan and Liphardt, Schuyler and Losecaat Vermeer, Annabel and Love, Bradley and Mack, Michael and Malpica, Norberto and Marins, Theo and Maumet, Camille and McDonald, Kelsey and McGuire, Joseph and Melero, Helena and Méndez Leal, Adriana and Meyer, Benjamin and Meyer, Kristin and Mihai, Paul and Mitsis, Georgios and Moll, Jorge and Nielson, Dylan and Nilsonne, Gustav and Notter, Michael and Olivetti, Emanuele and Onicas, Adrian and Papale, Paolo and Patil, Kaustubh and Peelle, Jonathan E. and Pérez, Alexandre and Pischedda, Doris and Poline, Jean-Baptiste and Prystauka, Yanina and Ray, Shruti and Reuter-Lorenz, Patricia and Reynolds, Richard and Ricciardi, Emiliano and Rieck, Jenny and Rodriguez-Thompson, Anais and Romyn, Anthony and Salo, Taylor and Samanez-Larkin, Gregory and Sanz-Morales, Emilio and Schlichting, Margaret and Schultz, Douglas and Shen, Qiang and Sheridan, Margaret and Shiguang, Fu and Silvers, Jennifer and Skagerlund, Kenny and Smith, Alec and Smith, David and Sokol-Hessner, Peter and Steinkamp, Simon and Tashjian, Sarah and Thirion, Bertrand and Thorp, John and Tinghög, Gustav and Tisdall, Loreen and Tompson, Steven and Toro-Serey, Claudio and Torre, Juan and Tozzi, Leonardo and Truong, Vuong and Turella, Luca and van’t Veer, Anna E. and Verguts, Tom and Vettel, Jean and Vijayarajah, Sagana and Vo, Khoi and Wall, Matthew and Weeda, Wouter D. and Weis, Susanne and White, David and Wisniewski, David and Xifra-Porxas, Alba and Yearling, Emily and Yoon, Sangsuk and Yuan, Rui and Yuen, Kenneth and Zhang, Lei and Zhang, Xu and Zosky, Joshua and Nichols, Thomas E. and Poldrack, Russell A. and Schonberg, Tom}},\n  language     = {{eng}},\n  pages        = {{31}},\n  series       = {{bioRxiv}},\n  title        = {{Variability in the analysis of a single neuroimaging dataset by many teams}},\n  url          = {{https://www.biorxiv.org/content/10.1101/843193v1}},\n  year         = {{2019}},\n}\n\n

\n

\n\n\n\n\n\n

\n

\n \n 2018\n \n \n (7)\n \n \n

\n

\n \n \n

\n \n\n \n \n \n \n \n \n Signed reward prediction errors drive declarative learning.\n \n \n \n \n\n\n \n De Loof, Esther; Ergo, K.; Naert, L.; Janssens, C.; Talsma, D.; Van Opstal, F.; and Verguts, T.\n\n\n \n\n\n\n PLOS ONE, 13(1). 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Signed$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8544739,\n  articleno    = {{e0189212}},\n  author       = {{De Loof, Esther and Ergo, Kate and Naert, Lien and Janssens, Clio and Talsma, Durk and Van Opstal, Filip and Verguts, Tom}},\n  issn         = {{1932-6203}},\n  journal      = {{PLOS ONE}},\n  keywords     = {{declarative learning,signed reward prediction error,EEG,oscillatory signatures of reward processing}},\n  language     = {{eng}},\n  number       = {{1}},\n  publisher    = {{Public Library of Science (PLoS)}},\n  title        = {{Signed reward prediction errors drive declarative learning}},\n  url          = {{http://doi.org/10.1371/journal.pone.0189212}},\n  volume       = {{13}},\n  year         = {{2018}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Occipital alpha power reveals fast attentional inhibition of incongruent distractors.\n \n \n \n \n\n\n \n Janssens, Clio; De Loof, E.; Böhler, N.; Pourtois, G.; and Verguts, T.\n\n\n \n\n\n\n PSYCHOPHYSIOLOGY, 55(3). 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Occipital$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8550465,\n  articleno    = {{UNSP e13011}},\n  author       = {{Janssens, Clio and De Loof, Esther and Böhler, Nico and Pourtois, Gilles and Verguts, Tom}},\n  issn         = {{0048-5772}},\n  journal      = {{PSYCHOPHYSIOLOGY}},\n  keywords     = {{ACTION-MONITORING PROCESSES,ANTERIOR CINGULATE CORTEX,COGNITIVE CONTROL,VISUOSPATIAL ATTENTION,REPETITION SUPPRESSION,NEURAL MECHANISMS,CONFLICT,STIMULUS,TARGET,EEG}},\n  language     = {{eng}},\n  number       = {{3}},\n  title        = {{Occipital alpha power reveals fast attentional inhibition of incongruent distractors}},\n  url          = {{http://doi.org/10.1111/psyp.13011}},\n  volume       = {{55}},\n  year         = {{2018}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Task-relevant information modulates primary motor cortex activity before movement onset.\n \n \n \n \n\n\n \n Buc Calderon, Cristian; Van Opstal, F.; Peigneux, P.; Verguts, T.; and Gevers, W.\n\n\n \n\n\n\n FRONTIERS IN HUMAN NEUROSCIENCE, 12. 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Task-relevant$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8557824,\n  articleno    = {{93}},\n  author       = {{Buc Calderon, Cristian and Van Opstal, Filip and Peigneux, Phillippe and Verguts, Tom and Gevers, Wim}},\n  issn         = {{1662-5161}},\n  journal      = {{FRONTIERS IN HUMAN NEUROSCIENCE}},\n  keywords     = {{PERCEPTUAL DECISION-MAKING,DEVELOPING OCULOMOTOR COMMANDS,PARIETAL CORTEX,HUMAN BRAIN,RESPONSE COMPETITION,GENERAL MECHANISM,NEURAL RESPONSES,ACTION SELECTION,PREMOTOR CORTEX,AREA 7A}},\n  language     = {{eng}},\n  title        = {{Task-relevant information modulates primary motor cortex activity before movement onset}},\n  url          = {{http://doi.org/10.3389/fnhum.2018.00093}},\n  volume       = {{12}},\n  year         = {{2018}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Reduced distractor interference during vagus nerve stimulation.\n \n \n \n \n\n\n \n van Bochove, Marlies; De Taeye, L.; Raedt, R.; Vonck, K.; Meurs, A.; Boon, P.; Dauwe, I.; Notebaert, W.; and Verguts, T.\n\n\n \n\n\n\n INTERNATIONAL JOURNAL OF PSYCHOPHYSIOLOGY, 128: 93–99. 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Reduced$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8566500,\n  abstract     = {{Suppressing irrelevant information in decision making is an essential everyday skill. We studied whether this ability could be improved in epileptic patients during vagus nerve stimulation (VNS). VNS is known to increase norepinephrine (NE) in the brain. NE is thought to improve several aspects of cognitive control, including the suppression of irrelevant information. Nineteen epileptic VNS patients executed the Eriksen flanker task twice, both during on and off stimulation. Distractor interference was indexed by the congruency effect, a standard empirical marker of cognitive control. We found a reduced congruency effect during stimulation, which indicates an improved ability to suppress distractor interference. This effect was only found in patients that are clinically determined VNS-responders (n = 10). As VNS increases NE in VNS-responders, our finding suggests a beneficial role of NE in cognitive control. At the same time, it suggests that VNS does not only reduce seizure frequency in epileptic patients, but also improves cognitive control.}},\n  author       = {{van Bochove, Marlies and De Taeye, Leen and Raedt, Robrecht and Vonck, Kristl and Meurs, Alfred and Boon, Paul and Dauwe, Ine and Notebaert, Wim and Verguts, Tom}},\n  issn         = {{0167-8760}},\n  journal      = {{INTERNATIONAL JOURNAL OF PSYCHOPHYSIOLOGY}},\n  keywords     = {{THERAPY-RESISTANT EPILEPSY,LOCUS-COERULEUS LESIONS,COGNITIVE CONTROL,REFRACTORY EPILEPSY,PREFRONTAL CORTEX,NORADRENERGIC MODULATION,INDIVIDUAL-DIFFERENCES,ALZHEIMERS-DISEASE,ANTERIOR CINGULATE,HUMAN,NEOCORTEX,Cognitive control,Congruency effect,Vagus nerve stimulation (VNS),Norepinephrine (NE),Epilepsy}},\n  language     = {{eng}},\n  pages        = {{93--99}},\n  title        = {{Reduced distractor interference during vagus nerve stimulation}},\n  url          = {{http://doi.org/10.1016/j.ijpsycho.2018.03.015}},\n  volume       = {{128}},\n  year         = {{2018}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Human midcingulate cortex encodes distributed representations of task progress.\n \n \n \n \n\n\n \n Holroyd, Clay; Ribas-Fernandes, J. J. F.; Shahnazian, D.; Silvetti, M.; and Verguts, T.\n\n\n \n\n\n\n PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 115(25): 6398–6403. 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Human$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8567707,\n  abstract     = {{The function of midcingulate cortex (MCC) remains elusive despite decades of investigation and debate. Complicating matters, individual MCC neurons respond to highly diverse task-related events, and MCC activation is reported in most human neuroimaging studies employing a wide variety of task manipulations. Here we investigate this issue by applying a model-based cognitive neuroscience approach involving neural network simulations, functional magnetic resonance imaging, and representational similarity analysis. We demonstrate that human MCC encodes distributed, dynamically evolving representations of extended, goal-directed action sequences. These representations are uniquely sensitive to the stage and identity of each sequence, indicating that MCC sustains contextual information necessary for discriminating between task states. These results suggest that standard univariate approaches for analyzing MCC function overlook the major portion of task-related information encoded by this brain area and point to promising new avenues for investigation.}},\n  author       = {{Holroyd, Clay and Ribas-Fernandes, Jose J. F. and Shahnazian, Danesh and Silvetti, Massimo and Verguts, Tom}},\n  issn         = {{0027-8424}},\n  journal      = {{PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA}},\n  keywords     = {{ANTERIOR CINGULATE CORTEX,MEDIAL FRONTAL-CORTEX,PREFRONTAL CORTEX,UNIVARIATE ANALYSIS,COGNITIVE CONTROL,ACTION SEQUENCES,MULTI-VOXEL,MOTOR AREA,BEHAVIOR,NEURONS,midcingulate cortex,recurrent neural network,representational,similarity analysis,fMRI,sequence execution}},\n  language     = {{eng}},\n  number       = {{25}},\n  pages        = {{6398--6403}},\n  title        = {{Human midcingulate cortex encodes distributed representations of task progress}},\n  url          = {{http://doi.org/10.1073/pnas.1803650115}},\n  volume       = {{115}},\n  year         = {{2018}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Dorsal anterior cingulate-brainstem ensemble as a reinforcement meta-learner.\n \n \n \n \n\n\n \n Silvetti, Massimo; Vassena, E.; Abrahamse, E.; and Verguts, T.\n\n\n \n\n\n\n PLOS COMPUTATIONAL BIOLOGY, 14(8). 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Dorsal$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{8573686,\n  articleno    = {{e1006370}},\n  author       = {{Silvetti, Massimo and Vassena, Eliana and Abrahamse, Elger and Verguts, Tom}},\n  issn         = {{1553-7358}},\n  journal      = {{PLOS COMPUTATIONAL BIOLOGY}},\n  language     = {{eng}},\n  number       = {{8}},\n  title        = {{Dorsal anterior cingulate-brainstem ensemble as a reinforcement meta-learner}},\n  url          = {{http://doi.org/10.1371/journal.pcbi.1006370}},\n  volume       = {{14}},\n  year         = {{2018}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n The unfolding action model of initiation times, movement times, and movement paths.\n \n \n \n \n\n\n \n Calderon, Cristian Buc; Gevers, W.; and Verguts, T.\n\n\n \n\n\n\n PSYCHOLOGICAL REVIEW, 125(5): 785–805. 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"The$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{8577798,\n  author       = {{Calderon, Cristian Buc and Gevers, Wim and Verguts, Tom}},\n  issn         = {{0033-295X}},\n  journal      = {{PSYCHOLOGICAL REVIEW}},\n  language     = {{eng}},\n  number       = {{5}},\n  pages        = {{785--805}},\n  publisher    = {{American Psychological Association (APA)}},\n  title        = {{The unfolding action model of initiation times, movement times, and movement paths}},\n  url          = {{http://doi.org/10.1037/rev0000110}},\n  volume       = {{125}},\n  year         = {{2018}},\n}\n\n

\n

\n\n\n\n

\n\n\n\n\n\n

\n

\n \n 2017\n \n \n (8)\n \n \n

\n

\n \n \n

\n \n\n \n \n \n \n \n Computational models of cognitive control.\n \n \n \n\n\n \n Verguts, Tom\n\n\n \n\n\n\n In The Wiley handbook of cognitive control, pages 127–142. Wiley, 2017.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@incollection{8506723,\n  author       = {{Verguts, Tom}},\n  booktitle    = {{The Wiley handbook of cognitive control}},\n  isbn         = {{978-1-118-92054-1}},\n  language     = {{eng}},\n  pages        = {{127--142}},\n  publisher    = {{Wiley}},\n  title        = {{Computational models of cognitive control}},\n  year         = {{2017}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Beyond trial-by-trial adaptation : a quantification of the time scale of cognitive control.\n \n \n \n \n\n\n \n Aben, Bart; Verguts, T.; and Van den Bussche, E.\n\n\n \n\n\n\n JOURNAL OF EXPERIMENTAL PSYCHOLOGY-HUMAN PERCEPTION AND PERFORMANCE, 43(3): 509–517. 2017.\n \n\n\n\n
\n\n\n\n \n \n $\"Beyond$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{8517897,\n  author       = {{Aben, Bart and Verguts, Tom and Van den Bussche, Eva}},\n  issn         = {{0096-1523}},\n  journal      = {{JOURNAL OF EXPERIMENTAL PSYCHOLOGY-HUMAN PERCEPTION AND PERFORMANCE}},\n  language     = {{eng}},\n  number       = {{3}},\n  pages        = {{509--517}},\n  publisher    = {{American Psychological Association (APA)}},\n  title        = {{Beyond trial-by-trial adaptation : a quantification of the time scale of cognitive control}},\n  url          = {{http://doi.org/10.1037/xhp0000324}},\n  volume       = {{43}},\n  year         = {{2017}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n The time course of spatial attention shifts in elementary arithmetic.\n \n \n \n \n\n\n \n Liu, Dixiu; Cai, D.; Verguts, T.; and Chen, Q.\n\n\n \n\n\n\n SCIENTIFIC REPORTS, 7. 2017.\n \n\n\n\n
\n\n\n\n \n \n $\"The$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8520072,\n  articleno    = {{921}},\n  author       = {{Liu, Dixiu and Cai, Danni and Verguts, Tom and Chen, Qi}},\n  issn         = {{2045-2322}},\n  journal      = {{SCIENTIFIC REPORTS}},\n  keywords     = {{MENTAL NUMBER LINE,OPERATIONAL MOMENTUM,SUBTRACTION PROBLEMS,SPACE,REPRESENTATIONS,ASSOCIATIONS,MAGNITUDE,MOVEMENTS,COGNITION,LANGUAGE}},\n  language     = {{eng}},\n  title        = {{The time course of spatial attention shifts in elementary arithmetic}},\n  url          = {{http://doi.org/10.1038/s41598-017-01037-3}},\n  volume       = {{7}},\n  year         = {{2017}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Binding by random bursts : a computational model of cognitive control.\n \n \n \n \n\n\n \n Verguts, Tom\n\n\n \n\n\n\n JOURNAL OF COGNITIVE NEUROSCIENCE, 29(6): 1103–1118. 2017.\n \n\n\n\n
\n\n\n\n \n \n $\"Binding$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{8520763,\n  author       = {{Verguts, Tom}},\n  issn         = {{0898-929X}},\n  journal      = {{JOURNAL OF COGNITIVE NEUROSCIENCE}},\n  language     = {{eng}},\n  number       = {{6}},\n  pages        = {{1103--1118}},\n  publisher    = {{MIT Press}},\n  title        = {{Binding by random bursts : a computational model of cognitive control}},\n  url          = {{http://doi.org/10.1162/jocn_a_01117}},\n  volume       = {{29}},\n  year         = {{2017}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Numerical proportion representation : a neurocomputational account.\n \n \n \n \n\n\n \n Chen, Qi; and Verguts, T.\n\n\n \n\n\n\n FRONTIERS IN HUMAN NEUROSCIENCE, 11. 2017.\n \n\n\n\n
\n\n\n\n \n \n $\"Numerical$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8528831,\n  articleno    = {{412}},\n  author       = {{Chen, Qi and Verguts, Tom}},\n  issn         = {{1662-5161}},\n  journal      = {{FRONTIERS IN HUMAN NEUROSCIENCE}},\n  keywords     = {{PRIMATE POSTERIOR PARIETAL,OBJECT RECOGNITION,PREFRONTAL CORTEX,NUMBER SENSE,NEURAL MODEL,FRACTIONS,MONKEY,TRANSFORMATIONS,CONNECTIONIST,INFORMATION}},\n  language     = {{eng}},\n  title        = {{Numerical proportion representation : a neurocomputational account}},\n  url          = {{http://doi.org/10.3389/fnhum.2017.00412}},\n  volume       = {{11}},\n  year         = {{2017}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Dissociated spatial-arithmetic associations in horizontal and vertical dimensions.\n \n \n \n \n\n\n \n Liu, Dixiu; Verguts, T.; Li, M.; and Chen, Q.\n\n\n \n\n\n\n FRONTIERS IN PSYCHOLOGY, 8. 2017.\n \n\n\n\n
\n\n\n\n \n \n $\"Dissociated$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8533167,\n  articleno    = {{1741}},\n  author       = {{Liu, Dixiu and Verguts, Tom and Li, Megjin and Chen, Qi}},\n  issn         = {{1664-1078}},\n  journal      = {{FRONTIERS IN PSYCHOLOGY}},\n  keywords     = {{NUMBER LINE,OPERATIONAL MOMENTUM,ATTENTION,SHIFTS,SPACE,MOVEMENTS}},\n  language     = {{eng}},\n  title        = {{Dissociated spatial-arithmetic associations in horizontal and vertical dimensions}},\n  url          = {{http://doi.org/10.3389/fpsyg.2017.01741}},\n  volume       = {{8}},\n  year         = {{2017}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Continuous track paths reveal additive evidence integration in multistep decision making.\n \n \n \n \n\n\n \n Calderon, Cristian Buc; Dewulf, M.; Gevers, W.; and Verguts, T.\n\n\n \n\n\n\n PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 114(40): 10618–10623. 2017.\n \n\n\n\n
\n\n\n\n \n \n $\"Continuous$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{8533169,\n  author       = {{Calderon, Cristian Buc and Dewulf, Myrtille and Gevers, Wim and Verguts, Tom}},\n  issn         = {{0027-8424}},\n  journal      = {{PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA}},\n  language     = {{eng}},\n  number       = {{40}},\n  pages        = {{10618--10623}},\n  title        = {{Continuous track paths reveal additive evidence integration in multistep decision making}},\n  url          = {{http://doi.org/10.1073/pnas.1710913114}},\n  volume       = {{114}},\n  year         = {{2017}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Numerical cognition : learning binds biology to culture.\n \n \n \n \n\n\n \n Verguts, Tom; and Chen, Q.\n\n\n \n\n\n\n TRENDS IN COGNITIVE SCIENCES, 21(12): 913–914. 2017.\n \n\n\n\n
\n\n\n\n \n \n $\"Numerical$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8537959,\n  author       = {{Verguts, Tom and Chen, Qi}},\n  issn         = {{1364-6613}},\n  journal      = {{TRENDS IN COGNITIVE SCIENCES}},\n  keywords     = {{PRIMATE PREFRONTAL CORTEX,FLUTTER DISCRIMINATION,NUMBER,EVOLUTION,LANGUAGE}},\n  language     = {{eng}},\n  number       = {{12}},\n  pages        = {{913--914}},\n  title        = {{Numerical cognition : learning binds biology to culture}},\n  url          = {{http://doi.org/10.1016/j.tics.2017.09.004}},\n  volume       = {{21}},\n  year         = {{2017}},\n}\n\n

\n

\n\n\n\n

\n\n\n\n\n\n

\n

\n \n 2016\n \n \n (7)\n \n \n

\n

\n \n \n

\n \n\n \n \n \n \n \n \n The time course of cognitive control implementation.\n \n \n \n \n\n\n \n Janssens, Clio; De Loof, E.; Pourtois, G.; and Verguts, T.\n\n\n \n\n\n\n PSYCHONOMIC BULLETIN & REVIEW, 22(6): 1266–1272. 2016.\n \n\n\n\n
\n\n\n\n \n \n $\"The$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{7031916,\n  abstract     = {{Optimally recruiting cognitive control is a key factor in efficient task performance. In line with influential cognitive control theories, earlier work assumed that control is relatively slow. We challenge this notion and test whether control also can be implemented more rapidly by investigating the time course of cognitive control. In two experiments, a visual discrimination paradigm was applied. A reward cue was presented with variable intervals to target onset. The results showed that reward cues can rapidly improve performance. Importantly, the reward manipulation was orthogonal to the response, ensuring that the reward effect was due to fast cognitive control implementation rather than to automatic activation of rewarded S-R associations. We also empirically specify the temporal limits of cognitive control, because the reward cue had no effect when it was presented shortly after target onset, during task execution.}},\n  author       = {{Janssens, Clio and De Loof, Esther and Pourtois, Gilles and Verguts, Tom}},\n  issn         = {{1069-9384}},\n  journal      = {{PSYCHONOMIC BULLETIN & REVIEW}},\n  keywords     = {{REWARD PROSPECT,attention,cognitive control,reward,CONFLICT,TASK,INHIBITION,ACTIVATION,ATTENTION,INFORMATION,INTEGRATION,ADAPTATION}},\n  language     = {{eng}},\n  number       = {{6}},\n  pages        = {{1266--1272}},\n  title        = {{The time course of cognitive control implementation}},\n  url          = {{http://doi.org/10.3758/s13423-015-0992-3}},\n  volume       = {{22}},\n  year         = {{2016}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Event rate and reaction time performance in ADHD: testing predictions from the state regulation deficit hypothesis using an ex-Gaussian model.\n \n \n \n \n\n\n \n Metin, Baris; Wiersema, R.; Verguts, T.; Gasthuys, R.; van Der Meere, J.; Roeyers, H.; and Barke, E.\n\n\n \n\n\n\n CHILD NEUROPSYCHOLOGY, 22(1): 99–109. 2016.\n \n\n\n\n
\n\n\n\n \n \n $\"Event$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{7099828,\n  abstract     = {{According to the state regulation deficit (SRD) account, ADHD is associated with a problem using effort to maintain an optimal activation state under demanding task settings such as very fast or very slow event rates. This leads to a prediction of disrupted performance at event rate extremes reflected in higher Gaussian response variability that is a putative marker of activation during motor preparation. In the current study, we tested this hypothesis using ex-Gaussian modeling, which distinguishes Gaussian from non-Gaussian variability. Twenty-five children with ADHD and 29 typically developing controls performed a simple Go/No-Go task under four different event-rate conditions. There was an accentuated quadratic relationship between event rate and Gaussian variability in the ADHD group compared to the controls. The children with ADHD had greater Gaussian variability at very fast and very slow event rates but not at moderate event rates. The results provide evidence for the SRD account of ADHD. However, given that this effect did not explain all group differences (some of which were independent of event rate) other cognitive and/or motivational processes are also likely implicated in ADHD performance deficits.}},\n  author       = {{Metin, Baris and Wiersema, Roeljan and Verguts, Tom and Gasthuys, Roos and van Der Meere, JJ and Roeyers, Herbert and Barke, Edmund}},\n  issn         = {{0929-7049}},\n  journal      = {{CHILD NEUROPSYCHOLOGY}},\n  keywords     = {{HYPERACTIVITY,VARIABILITY,CHILDREN,DELAY AVERSION,ATTENTION-DEFICIT/HYPERACTIVITY DISORDER,DISTRIBUTIONS,COMPONENTS,SYMPTOMS,WORKING,CHOICE,ADHD,ex-Gaussian model,Reaction time,State regulation deficit,Event rate}},\n  language     = {{eng}},\n  number       = {{1}},\n  pages        = {{99--109}},\n  publisher    = {{ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD}},\n  title        = {{Event rate and reaction time performance in ADHD: testing predictions from the state regulation deficit hypothesis using an ex-Gaussian model}},\n  url          = {{http://doi.org/10.1080/09297049.2014.986082}},\n  volume       = {{22}},\n  year         = {{2016}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Predictive information speeds up visual awareness in an individuation task by modulating threshold setting, not processing efficiency.\n \n \n \n \n\n\n \n De Loof, Esther; Van Opstal, F.; and Verguts, T.\n\n\n \n\n\n\n VISION RESEARCH, 121: 104–112. 2016.\n \n\n\n\n
\n\n\n\n \n \n $\"Predictive$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{7146583,\n  author       = {{De Loof, Esther and Van Opstal, Filip and Verguts, Tom}},\n  editor       = {{Alais, David}},\n  issn         = {{0042-6989}},\n  journal      = {{VISION RESEARCH}},\n  keywords     = {{PRIOR PROBABILITY,CONSCIOUSNESS,NEURAL MECHANISMS,SPATIAL ATTENTION,PERCEPTUAL DECISIONS,DIFFUSION-MODEL ANALYSIS,CORTEX,BRAIN,EXPECTATION,ORIENTATION,Visual awareness,Individuation,Identification,Drift diffusion model,Predictive information,Awareness threshold}},\n  language     = {{eng}},\n  pages        = {{104--112}},\n  title        = {{Predictive information speeds up visual awareness in an individuation task by modulating threshold setting, not processing efficiency}},\n  url          = {{http://doi.org/10.1016/j.visres.2016.03.002}},\n  volume       = {{121}},\n  year         = {{2016}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Paying attention to working memory: similarities in the spatial distribution of attention in mental and physical space.\n \n \n \n \n\n\n \n Sahan, Muhammet Ikbal; Verguts, T.; Böhler, N.; Pourtois, G.; and Fias, W.\n\n\n \n\n\n\n PSYCHONOMIC BULLETIN & REVIEW, 23(4): 1190–1197. 2016.\n \n\n\n\n
\n\n\n\n \n \n $\"Paying$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{7197325,\n  abstract     = {{Selective attention is not limited to information that is physically present in the external world, but can also operate on mental representations in the internal world.  However, it is not known whether mechanisms of attentional selection in mental space operate in a similar fashion as in physical space.  We studied the spatial distribution of attention for items in physical and in mental space by comparing how successfully distracters were rejected at varying distances from the attended location.  The results indicate very similar distribution characteristics of spatial attention in physical and mental space.  Specifically, we found that performance monotonically improved with increasing distracter distance relative to the attended location suggesting that distracter confusability is particularly pronounced for nearby distracters relative to further away distracters.  The present findings suggest that mental representations preserve their spatial configuration in working memory, and that similar mechanistic principles underlie selective attention in physical and mental space.}},\n  author       = {{Sahan, Muhammet Ikbal and Verguts, Tom and Böhler, Nico and Pourtois, Gilles and Fias, Wim}},\n  issn         = {{1069-9384}},\n  journal      = {{PSYCHONOMIC BULLETIN & REVIEW}},\n  keywords     = {{distribution,orienting,distracter confusion,mental representations,spatial attention,working memory,SELECTIVE ATTENTION,SUPPRESSION,VISION}},\n  language     = {{eng}},\n  number       = {{4}},\n  pages        = {{1190--1197}},\n  title        = {{Paying attention to working memory: similarities in the spatial distribution of attention in mental and physical space}},\n  url          = {{http://doi.org/10.3758/s13423-015-0990-5}},\n  volume       = {{23}},\n  year         = {{2016}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Grounding cognitive control in associative learning.\n \n \n \n \n\n\n \n Abrahamse, Elger; Braem, S.; Notebaert, W.; and Verguts, T.\n\n\n \n\n\n\n PSYCHOLOGICAL BULLETIN, 142(7): 693–728. 2016.\n \n\n\n\n
\n\n\n\n \n \n $\"Grounding$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{7209063,\n  abstract     = {{Cognitive control covers a broad range of cognitive functions, but its research and theories typically remain tied to a single domain. Here we outline and review an associative learning perspective on cognitive control in which control emerges from associative networks containing perceptual, motor, and goal representations. Our review identifies 3 trending research themes that are shared between the domains of conflict adaptation, task switching, response inhibition, and attentional control: Cognitive control is context-specific, can operate in the absence of awareness, and is modulated by reward. As these research themes can be envisaged as key characteristics of learning, we propose that their joint emergence across domains is not coincidental but rather reflects a (latent) growth of interest in learning-based control. Associative learning has the potential for providing broad-scaled integration to cognitive control theory, and offers a promising avenue for understanding cognitive control as a self-regulating system without postulating an ill-defined set of homunculi. We discuss novel predictions, theoretical implications, and immediate challenges that accompany an associative learning perspective on cognitive control.}},\n  author       = {{Abrahamse, Elger and Braem, Senne and Notebaert, Wim and Verguts, Tom}},\n  issn         = {{0033-2909}},\n  journal      = {{PSYCHOLOGICAL BULLETIN}},\n  keywords     = {{CONTEXT-SPECIFIC CONTROL,DRIVEN ATTENTIONAL CAPTURE,ITEM-SPECIFIC CONTROL,TRIGGERED RESPONSE-INHIBITION,IRRELEVANT STIMULUS FEATURES,ANTERIOR CINGULATE CORTEX,EVENT-RELATED POTENTIALS,STOP-SIGNAL TASK,STROOP-LIKE TASK,TOP-DOWN CONTROL,attentional control,cognitive control,conflict adaptation,response inhibition,task switching}},\n  language     = {{eng}},\n  number       = {{7}},\n  pages        = {{693--728}},\n  title        = {{Grounding cognitive control in associative learning}},\n  url          = {{http://doi.org/10.1037/bul0000047}},\n  volume       = {{142}},\n  year         = {{2016}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Unimodal and cross-modal prediction is enhanced in musicians.\n \n \n \n \n\n\n \n Vassena, Eliana; Kochman, K.; Latomme, J.; and Verguts, T.\n\n\n \n\n\n\n SCIENTIFIC REPORTS, 6: 7. 2016.\n \n\n\n\n
\n\n\n\n \n \n $\"Unimodal$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{7235073,\n  abstract     = {{Musical training involves exposure to complex auditory and visual stimuli, memorization of elaborate sequences, and extensive motor rehearsal. It has been hypothesized that such multifaceted training may be associated with differences in basic cognitive functions, such as prediction, potentially translating to a facilitation in expert musicians. Moreover, such differences might generalize to non-auditory stimuli. This study was designed to test both hypotheses. We implemented a cross-modal attentional cueing task with auditory and visual stimuli, where a target was preceded by compatible or incompatible cues in mainly compatible (80% compatible, predictable) or random blocks (50% compatible, unpredictable). This allowed for the testing of prediction skills in musicians and controls. Musicians showed increased sensitivity to the statistical structure of the block, expressed as advantage for compatible trials (disadvantage for incompatible trials), but only in the mainly compatible (predictable) blocks. Controls did not show this pattern. The effect held within modalities (auditory, visual), across modalities, and when controlling for short-term memory capacity. These results reveal a striking enhancement in cross-modal prediction in musicians in a very basic cognitive task.}},\n  articleno    = {{25225}},\n  author       = {{Vassena, Eliana and Kochman, Katty and Latomme, Julie and Verguts, Tom}},\n  issn         = {{2045-2322}},\n  journal      = {{SCIENTIFIC REPORTS}},\n  keywords     = {{BEHAVIOR,PERFORMANCE,BENEFIT,ERRORS,TASK,PERCEPTION,BRAIN PLASTICITY,OPERA HYPOTHESIS,MUSICAL EXPERTISE}},\n  language     = {{eng}},\n  pages        = {{7}},\n  publisher    = {{NATURE PUBLISHING GROUP}},\n  title        = {{Unimodal and cross-modal prediction is enhanced in musicians}},\n  url          = {{http://doi.org/10.1038/srep25225}},\n  volume       = {{6}},\n  year         = {{2016}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Spontaneous eyeblinks during breaking continuous flash suppression are associated with increased detection times.\n \n \n \n \n\n\n \n Van Opstal, Filip; De Loof, E.; Verguts, T.; and Cleeremans, A.\n\n\n \n\n\n\n JOURNAL OF VISION, 16(14). 2016.\n \n\n\n\n
\n\n\n\n \n \n $\"Spontaneous$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8503266,\n  articleno    = {{21}},\n  author       = {{Van Opstal, Filip and De Loof, Esther and Verguts, Tom and Cleeremans, Axel}},\n  issn         = {{1534-7362}},\n  journal      = {{JOURNAL OF VISION}},\n  keywords     = {{STRIATAL DOPAMINE,INDIVIDUAL-DIFFERENCES,VISUAL AWARENESS,COGNITIVE LOAD,EYE BLINKS,WORDS,CONSCIOUSNESS,MOVEMENTS,STIMULI,TASKS}},\n  language     = {{eng}},\n  number       = {{14}},\n  publisher    = {{Association for Research in Vision and Ophthalmology (ARVO)}},\n  title        = {{Spontaneous eyeblinks during breaking continuous flash suppression are associated with increased detection times}},\n  url          = {{http://doi.org/10.1167/16.14.21}},\n  volume       = {{16}},\n  year         = {{2016}},\n}\n\n

\n

\n\n\n\n

\n\n\n\n\n\n

\n

\n \n 2015\n \n \n (6)\n \n \n

\n

\n \n \n

\n \n\n \n \n \n \n \n \n No pain, no gain: the affective valence of congruency conditions changes following a successful response.\n \n \n \n \n\n\n \n Schouppe, Nathalie; Braem, S.; De Houwer, J.; Silvetti, M.; Verguts, T.; Ridderinkhof, R.; and Notebaert, W.\n\n\n \n\n\n\n COGNITIVE AFFECTIVE & BEHAVIORAL NEUROSCIENCE, 15(1): 251–261. 2015.\n \n\n\n\n
\n\n\n\n \n \n $\"No$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{5695403,\n  abstract     = {{The cognitive control theory of Botvinick, Cognitive, Affective, & Behavioral Neuroscience, 7, 356–366 (2007) integrates cognitive and affective control processes by emphasizing the aversive nature of cognitive conflict. Using an affective priming paradigm, we replicate earlier results showing that incongruent trials, relative to congruent trials, are indeed perceived as more aversive (Dreisbach & Fischer, Brain and Cognition, 78(2), 94–98 (2012)). Importantly, however, in two experiments we demonstrate that this effect is reversed following successful responses; correctly responding to incongruent trials engendered relatively more positive affect than correctly responding to congruent trials. The results are discussed in light of a recent computational model by Silvetti, Seurinck, and Verguts, Frontiers in Human Neuroscience, 5:75 (2011) where it is assumed that outcome expectancies are more negative for incongruent trials than congruent trials. Consequently, the intrinsic reward (prediction error) following successful completion is larger for incongruent than congruent trials. These findings divulge a novel perspective on 'cognitive' adaptations to conflict.}},\n  author       = {{Schouppe, Nathalie and Braem, Senne and De Houwer, Jan and Silvetti, Massimo and Verguts, Tom and Ridderinkhof, Richard and Notebaert, Wim}},\n  issn         = {{1530-7026}},\n  journal      = {{COGNITIVE AFFECTIVE & BEHAVIORAL NEUROSCIENCE}},\n  keywords     = {{Anterior cingulate cortex,MODULATES COGNITIVE CONTROL,Conflict adaptation,Intrinsic reward,Reward prediction error,Affective priming,Conflict,Cognitive control,CONTINGENCY,INTERFERENCE,COMPATIBILITY,JUSTIFICATION,INTEGRATION,TASK,CINGULATE CORTEX,STIMULUS-RESPONSE,CONFLICT ADAPTATION}},\n  language     = {{eng}},\n  number       = {{1}},\n  pages        = {{251--261}},\n  title        = {{No pain, no gain: the affective valence of congruency conditions changes following a successful response}},\n  url          = {{http://doi.org/10.3758/s13415-014-0318-3}},\n  volume       = {{15}},\n  year         = {{2015}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Dysfunctional modulation of default mode network activity in attention-deficit/hyperactivity disorder.\n \n \n \n \n\n\n \n Metin, Baris; Krebs, R.; Wiersema, R.; Verguts, T.; Gasthuys, R.; Van der Meere, J.; Achten, E.; Roeyers, H.; and Barke, E.\n\n\n \n\n\n\n JOURNAL OF ABNORMAL PSYCHOLOGY, 124(1): 208–214. 2015.\n \n\n\n\n
\n\n\n\n \n \n $\"Dysfunctional$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{5934876,\n  abstract     = {{The state regulation deficit model posits that individuals with attention-deficit/hyperactivity disorder (ADHD) have difficulty applying mental effort effectively under suboptimal conditions such as very fast and very slow event rates (ERs). ADHD is also associated with diminished suppression of default mode network (DMN) activity and related performance deficits on tasks requiring effortful engagement. The current study builds on these 2 literatures to test the hypothesis that failure to modulate DMN activity in ADHD might be especially pronounced at ER extremes. Nineteen adults with ADHD and 20 individuals without any neuropsychiatric condition successfully completed a simple target detection task under 3 ER conditions (2-, 4-, and 8-s interstimulus intervals) inside the scanner. Task-related DMN deactivations were compared between 2 groups. There was a differential effect of ER on DMN activity for individuals with ADHD compared to controls. Individuals with ADHD displayed excessive DMN activity at the fast and slow, but not at the moderate ER. The results indicate that DMN attenuation in ADHD is disrupted in suboptimal energetic states where additional effort is required to optimize task engagement. DMN dysregulation may be an important element of the neurobiological underpinnings of state regulation deficits in ADHD.}},\n  author       = {{Metin, Baris and Krebs, Ruth and Wiersema, Roeljan and Verguts, Tom and Gasthuys, Roos and Van der Meere, Jacob and Achten, Eric and Roeyers, Herbert and Barke, Edmund}},\n  issn         = {{0021-843X}},\n  journal      = {{JOURNAL OF ABNORMAL PSYCHOLOGY}},\n  keywords     = {{ADHD,RELIABILITY,STATE,METHYLPHENIDATE,SCALE,TASK,BRAIN,EVENT RATE,PERFORMANCE,event rate,MRI,ADHD,default mode network,state regulation deficit,fMRI}},\n  language     = {{eng}},\n  number       = {{1}},\n  pages        = {{208--214}},\n  title        = {{Dysfunctional modulation of default mode network activity in attention-deficit/hyperactivity disorder}},\n  url          = {{http://doi.org/10.1037/abn0000013}},\n  volume       = {{124}},\n  year         = {{2015}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Adaptive effort investment in cognitive and physical tasks: a neurocomputational model.\n \n \n \n \n\n\n \n Verguts, Tom; Vassena, E.; and Silvetti, M.\n\n\n \n\n\n\n FRONTIERS IN BEHAVIORAL NEUROSCIENCE, 9: 17. 2015.\n \n\n\n\n
\n\n\n\n \n \n $\"Adaptive$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{5948160,\n  abstract     = {{Despite its importance in everyday life, the computational nature of effort investment remains poorly understood. We propose an effort model obtained from optimality considerations, and a neurocomputational approximation to the optimal model. Both are couched in the framework of reinforcement learning. It is shown that choosing when or when not to exert effort can be adaptively learned, depending on rewards, costs, and task difficulty. In the neurocomputational model, the limbic loop comprising anterior cingulate cortex (ACC) and ventral striatum in the basal ganglia allocates effort to cortical stimulus-action pathways whenever this is valuable. We demonstrate that the model approximates optimality. Next, we consider two hallmark effects from the cognitive control literature, namely proportion congruency and sequential congruency effects. It is shown that the model exerts both proactive and reactive cognitive control. Then, we simulate two physical effort tasks. In line with empirical work, impairing the model's dopaminergic pathway leads to apathetic behavior. Thus, we conceptually unify the exertion of cognitive and physical effort, studied across a variety of literatures (e.g., motivation and cognitive control) and animal species.}},\n  articleno    = {{57}},\n  author       = {{Verguts, Tom and Vassena, Eliana and Silvetti, Massimo}},\n  issn         = {{1662-5153}},\n  journal      = {{FRONTIERS IN BEHAVIORAL NEUROSCIENCE}},\n  keywords     = {{computational model,cognitive effort,cognitive control,PREFRONTAL CORTEX,COMPUTATIONAL MODEL,INTEGRATIVE THEORY,DOPAMINERGIC MIDBRAIN,ANTERIOR CINGULATE CORTEX,MEDIAL FRONTAL-CORTEX,DECISION-MAKING,CONFLICT-ADAPTATION,BASAL GANGLIA,physical effort,NUCLEUS-ACCUMBENS}},\n  language     = {{eng}},\n  pages        = {{17}},\n  title        = {{Adaptive effort investment in cognitive and physical tasks: a neurocomputational model}},\n  url          = {{http://doi.org/10.3389/fnbeh.2015.0005}},\n  volume       = {{9}},\n  year         = {{2015}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Losing the boundary: cognition biases action well after action selection.\n \n \n \n \n\n\n \n Calderon, CB; Verguts, T.; and Gevers, W\n\n\n \n\n\n\n JOURNAL OF EXPERIMENTAL PSYCHOLOGY-GENERAL, 144(4): 737–743. 2015.\n \n\n\n\n
\n\n\n\n \n \n $\"Losing$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{6907785,\n  abstract     = {{For selecting an action, traditional theories suggest a cognitive architecture made of serial processing units. Others suggested that action selection emerges from the parallel implementation of and competition between multiple action plans. To disentangle these 2 hypotheses, we created a reaching task assessing the temporal dynamics of action selection. Crucially, our design did not force action selection processes to operate in parallel, allowing an informative comparison between the hypotheses. We manipulated the probability of congruence between a cue and a delayed reach target to investigate, in an unbiased way, whether congruence probability interacts with reach trajectory. Our results show that reach trajectories are modulated by the probability of congruence. Hence, action selection is temporally spread, continues after movement onset, and emerges from a competition between multiple afforded action plans, in parallel biased by relevant task factors (e.g., probability of reach).}},\n  author       = {{Calderon, CB and Verguts, Tom and Gevers, W}},\n  issn         = {{0096-3445}},\n  journal      = {{JOURNAL OF EXPERIMENTAL PSYCHOLOGY-GENERAL}},\n  keywords     = {{MOVEMENT PREPARATION,DYNAMIC FIELD-THEORY,DECISION-MAKING,CORTICOSPINAL EXCITABILITY,NEURAL MECHANISMS,PREMOTOR CORTEX,PARIETAL CORTEX,VISUAL-SEARCH,MOTOR SYSTEM,TRAJECTORIES,decision making,action selection,movement planning,parallel processing,reaching}},\n  language     = {{eng}},\n  number       = {{4}},\n  pages        = {{737--743}},\n  publisher    = {{AMER PSYCHOLOGICAL ASSOC}},\n  title        = {{Losing the boundary: cognition biases action well after action selection}},\n  url          = {{http://doi.org/10.1037/xge0000087}},\n  volume       = {{144}},\n  year         = {{2015}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n Basic number representation and beyond: neuroimaging and computational modeling.\n \n \n \n\n\n \n Roggeman, Chantal; Fias, W.; and Verguts, T.\n\n\n \n\n\n\n In Oxford handbook of numerical cognition, of Oxford Library of Psychology, pages 567–583. Oxford University Press, 2015.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@incollection{6914238,\n  author       = {{Roggeman, Chantal and Fias, Wim and Verguts, Tom}},\n  booktitle    = {{Oxford handbook of numerical cognition}},\n  isbn         = {{9780199642342}},\n  language     = {{eng}},\n  pages        = {{567--583}},\n  publisher    = {{Oxford University Press}},\n  series       = {{Oxford Library of Psychology}},\n  title        = {{Basic number representation and beyond: neuroimaging and computational modeling}},\n  year         = {{2015}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Unsigned value prediction-error modulates the motor system in absence of choice.\n \n \n \n \n\n\n \n Vassena, Eliana; Cobbaert, S.; Andres, M.; Fias, W.; and Verguts, T.\n\n\n \n\n\n\n NEUROIMAGE, 122: 73–79. 2015.\n \n\n\n\n
\n\n\n\n \n \n $\"Unsigned$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{6980975,\n  author       = {{Vassena, Eliana and Cobbaert, Stephanie and Andres, Michael and Fias, Wim and Verguts, Tom}},\n  issn         = {{1053-8119}},\n  journal      = {{NEUROIMAGE}},\n  keywords     = {{MEP,NEED,TMS,Prediction-error,TRANSCRANIAL MAGNETIC STIMULATION,Effort,DECISION-MAKING,Value,HUMAN BRAIN,ANTERIOR CINGULATE CORTEX,CORTICOSPINAL EXCITABILITY,INTEGRATIVE THEORY,COGNITION,MODEL,REWARD,Reward}},\n  language     = {{eng}},\n  pages        = {{73--79}},\n  title        = {{Unsigned value prediction-error modulates the motor system in absence of choice}},\n  url          = {{http://doi.org/10.1016/j.neuroimage.2015.07.081}},\n  volume       = {{122}},\n  year         = {{2015}},\n}\n\n

\n

\n\n\n\n

\n\n\n\n\n\n

\n

\n \n 2014\n \n \n (8)\n \n \n

\n

\n \n \n

\n \n\n \n \n \n \n \n \n A delta-rule model of numerical and non-numerical order processing.\n \n \n \n \n\n\n \n Verguts, Tom; and Van Opstal, F.\n\n\n \n\n\n\n JOURNAL OF EXPERIMENTAL PSYCHOLOGY: HUMAN PERCEPTION AND PERFORMANCE, 40(3): 1092–1102. 2014.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{4166111,\n  abstract     = {{Numerical and non-numerical order processing share empirical characteristics (distance effect and semantic congruity), but there are also important differences (in size effect and end effect). At the same time, models and theories of numerical and non-numerical order processing developed largely separately. Currently, we combine insights from 2 earlier models to integrate them in a common framework. We argue that the same learning principle underlies numerical and non-numerical orders, but that environmental features determine the empirical differences. Implications for current theories on order processing are pointed out.}},\n  author       = {{Verguts, Tom and Van Opstal, Filip}},\n  issn         = {{0096-1523}},\n  journal      = {{JOURNAL OF EXPERIMENTAL PSYCHOLOGY: HUMAN PERCEPTION AND PERFORMANCE}},\n  keywords     = {{computational modeling,learning,non-numerical orders,numerical cognition,BRAIN,MAGNITUDE,NEURAL MODEL,DIGIT NUMBERS,WORKING-MEMORY,PARIETAL CORTEX,DECISION-MAKING,TRANSITIVE INFERENCE,COMPARATIVE JUDGMENTS,NUMBER REPRESENTATION}},\n  language     = {{eng}},\n  number       = {{3}},\n  pages        = {{1092--1102}},\n  title        = {{A delta-rule model of numerical and non-numerical order processing}},\n  url          = {{http://doi.org/10.1037/a0035114}},\n  volume       = {{40}},\n  year         = {{2014}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Reward expectation and prediction error in human medial frontal cortex : an EEG study.\n \n \n \n \n\n\n \n Silvetti, Massimo; Nunez Castellar, E. P.; Roger, C.; and Verguts, T.\n\n\n \n\n\n\n NEUROIMAGE, 84: 376–382. 2014.\n \n\n\n\n
\n\n\n\n \n \n $\"Reward$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{4182572,\n  author       = {{Silvetti, Massimo and Nunez Castellar, Elena Patricia and Roger, Clémence and Verguts, Tom}},\n  issn         = {{1053-8119}},\n  journal      = {{NEUROIMAGE}},\n  keywords     = {{Prediction error,Medial frontal cortex,Reinforcement learning,Reward,ACC,VARIATION CNV,REACTION-TIME,ERP COMPONENTS,RESPONSE ERRORS,BRAIN POTENTIALS,PREFRONTAL CORTEX,NEURAL REPRESENTATION,ANTERIOR CINGULATE CORTEX,INDEPENDENT COMPONENT ANALYSIS,CONTINGENT NEGATIVE-VARIATION}},\n  language     = {{eng}},\n  pages        = {{376--382}},\n  title        = {{Reward expectation and prediction error in human medial frontal cortex : an EEG study}},\n  url          = {{http://doi.org/10.1016/j.neuroimage.2013.08.058}},\n  volume       = {{84}},\n  year         = {{2014}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Context-specific control and context selection in conflict tasks.\n \n \n \n \n\n\n \n Schouppe, Nathalie; Ridderinkhof, R.; Verguts, T.; and Notebaert, W.\n\n\n \n\n\n\n ACTA PSYCHOLOGICA, 146: 63–66. 2014.\n \n\n\n\n
\n\n\n\n \n \n $\"Context-specific$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{4218157,\n  author       = {{Schouppe, Nathalie and Ridderinkhof, Richard and Verguts, Tom and Notebaert, Wim}},\n  issn         = {{0001-6918}},\n  journal      = {{ACTA PSYCHOLOGICA}},\n  keywords     = {{AVOIDANCE,INTERFERENCE,DECISION-MAKING,COGNITIVE CONTROL,Response conflict,Avoidance,Context-specific control,Decision-making}},\n  language     = {{eng}},\n  pages        = {{63--66}},\n  publisher    = {{Elsevier}},\n  title        = {{Context-specific control and context selection in conflict tasks}},\n  url          = {{http://doi.org/10.1016/j.actpsy.2013.11.010}},\n  volume       = {{146}},\n  year         = {{2014}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n From conflict management to reward-based decision making: actors and critics in primate medial frontal cortex.\n \n \n \n\n\n \n Silvetti, Massimo; Alexander, W.; Verguts, T.; and Brown, J.\n\n\n \n\n\n\n NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS, 46: 44–57. 2014.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{4227314,\n  author       = {{Silvetti, Massimo and Alexander, William and Verguts, Tom and Brown, Joshua}},\n  issn         = {{0149-7634}},\n  journal      = {{NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS}},\n  language     = {{eng}},\n  pages        = {{44--57}},\n  title        = {{From conflict management to reward-based decision making: actors and critics in primate medial frontal cortex}},\n  volume       = {{46}},\n  year         = {{2014}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Correlation between individual differences in striatal dopamine and in visual consciousness.\n \n \n \n \n\n\n \n Van Opstal, Filip; Van Laeken, N.; Verguts, T.; van Dijck, J.; De Vos, F.; Goethals, I.; and Fias, W.\n\n\n \n\n\n\n CURRENT BIOLOGY, 24(7): R265–R266. 2014.\n \n\n\n\n
\n\n\n\n \n \n $\"Correlation$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n\n\n\n

\n

@article{4262408,\n  author       = {{Van Opstal, Filip and Van Laeken, Nick and Verguts, Tom and van Dijck, Jean-Philippe and De Vos, Filip and Goethals, Ingeborg and Fias, Wim}},\n  issn         = {{0960-9822}},\n  journal      = {{CURRENT BIOLOGY}},\n  keywords     = {{WORKING-MEMORY}},\n  language     = {{eng}},\n  number       = {{7}},\n  pages        = {{R265--R266}},\n  title        = {{Correlation between individual differences in striatal dopamine and in visual consciousness}},\n  url          = {{http://doi.org/10.1016/j.cub.2014.02.001}},\n  volume       = {{24}},\n  year         = {{2014}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n The P3 event-related potential is a biomarker for the efficacy of vagus nerve stimulation in patients with epilepsy.\n \n \n \n \n\n\n \n De Taeye, Leen; Vonck, K.; van Bochove, M.; Boon, P.; Van Roost, D.; Mollet, L.; Meurs, A.; De Herdt, V.; Carrette, E.; Dauwe, I.; Gadeyne, S.; van Mierlo, P.; Verguts, T.; and Raedt, R.\n\n\n \n\n\n\n NEUROTHERAPEUTICS, 11(3): 612–622. 2014.\n \n\n\n\n
\n\n\n\n \n \n $\"The$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{4358315,\n  abstract     = {{Currently, the mechanism of action of vagus nerve stimulation (VNS) is not fully understood, and it is unclear which factors determine a patient’s response to treatment. Recent preclinical experiments indicate that activation of the locus coeruleus noradrenergic system is critical for the antiepileptic effect of VNS. This study aims to evaluate the effect of VNS on noradrenergic signaling in the human brain through a noninvasive marker of locus coeruleus noradrenergic activity: the P3 component of the event-related potential. We investigated whether VNS differentially modulates the P3 component in VNS responders versus VNS nonresponders. For this purpose, we recruited 20 patients with refractory epilepsy who had been treated with VNS for at least 18 months. Patients were divided into 2 groups with regard to their reduction in mean monthly seizure frequency: 10 responders (>50 %) and 10 nonresponders (≤50 %). Two stimulation conditions were compared: VNS OFF and VNS ON. In each condition, the P3 component was measured during an auditory oddball paradigm. VNS induced a significant increase of the P3 amplitude at the parietal midline electrode, in VNS responders only. In addition, logistic regression analysis showed that the increase of P3 amplitude can be used as a noninvasive indicator for VNS responders. These results support the hypothesis that activation of the locus coeruleus noradrenergic system is associated with the antiepileptic effect of VNS. Modulation of the P3 amplitude should be further investigated as a noninvasive biomarker for the therapeutic efficacy of VNS in patients with refractory epilepsy.}},\n  author       = {{De Taeye, Leen and Vonck, Kristl and van Bochove, Marlies and Boon, Paul and Van Roost, Dirk and Mollet, Lies and Meurs, Alfred and De Herdt, Veerle and Carrette, Evelien and Dauwe, Ine and Gadeyne, Stefanie and van Mierlo, Pieter and Verguts, Tom and Raedt, Robrecht}},\n  issn         = {{1933-7213}},\n  journal      = {{NEUROTHERAPEUTICS}},\n  keywords     = {{epilepsy,event-related potentials,P3,biomarker,CHILDREN,SEIZURES,Vagus nerve stimulation,INTEGRATIVE THEORY,LONG-TERM,LOCUS-COERULEUS LESIONS,REFRACTORY EPILEPSY,TREATMENT-RESISTANT DEPRESSION,RAT-BRAIN,NOREPINEPHRINE,COGNITION,norepinephrine}},\n  language     = {{eng}},\n  number       = {{3}},\n  pages        = {{612--622}},\n  title        = {{The P3 event-related potential is a biomarker for the efficacy of vagus nerve stimulation in patients with epilepsy}},\n  url          = {{http://doi.org/10.1007/s13311-014-0272-3}},\n  volume       = {{11}},\n  year         = {{2014}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Overlapping neural systems represent cognitive effort and reward anticipation.\n \n \n \n \n\n\n \n Vassena, Eliana; Silvetti, M.; Böhler, N.; Achten, E.; Fias, W.; and Verguts, T.\n\n\n \n\n\n\n PLOS ONE, 9(3): 9. 2014.\n \n\n\n\n
\n\n\n\n \n \n $\"Overlapping$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{4368488,\n  abstract     = {{Anticipating a potential benefit and how difficult it will be to obtain it are valuable skills in a constantly changing environment. In the human brain, the anticipation of reward is encoded by the Anterior Cingulate Cortex (ACC) and Striatum. Naturally, potential rewards have an incentive quality, resulting in a motivational effect improving performance. Recently it has been proposed that an upcoming task requiring effort induces a similar anticipation mechanism as reward, relying on the same cortico-limbic network. However, this overlapping anticipatory activity for reward and effort has only been investigated in a perceptual task. Whether this generalizes to high-level cognitive tasks remains to be investigated. To this end, an fMRI experiment was designed to investigate anticipation of reward and effort in cognitive tasks. A mental arithmetic task was implemented, manipulating effort (difficulty), reward, and delay in reward delivery to control for temporal confounds. The goal was to test for the motivational effect induced by the expectation of bigger reward and higher effort. The results showed that the activation elicited by an upcoming difficult task overlapped with higher reward prospect in the ACC and in the striatum, thus highlighting a pivotal role of this circuit in sustaining motivated behavior.}},\n  articleno    = {{e91008}},\n  author       = {{Vassena, Eliana and Silvetti, Massimo and Böhler, Nico and Achten, Eric and Fias, Wim and Verguts, Tom}},\n  issn         = {{1932-6203}},\n  journal      = {{PLOS ONE}},\n  keywords     = {{BRAIN ACTIVATION,INDIVIDUAL-DIFFERENCES,MENTAL FATIGUE,DELAYED REWARDS,DECISION-MAKING,RAPHE SEROTONIN NEURONS,MEDIAL PREFRONTAL CORTEX,ACUTE TRYPTOPHAN DEPLETION,ANTERIOR CINGULATE CORTEX,NUCLEUS-ACCUMBENS DOPAMINE}},\n  language     = {{eng}},\n  number       = {{3}},\n  pages        = {{9}},\n  title        = {{Overlapping neural systems represent cognitive effort and reward anticipation}},\n  url          = {{http://doi.org/10.1371/journal.pone.0091008}},\n  volume       = {{9}},\n  year         = {{2014}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Dissociating contributions of ACC and vmPFC in reward prediction, outcome and choice.\n \n \n \n \n\n\n \n Vassena, Eliana; Krebs, R.; Silvetti, M.; Fias, W.; and Verguts, T.\n\n\n \n\n\n\n NEUROPSYCHOLOGIA, 59: 112–123. 2014.\n \n\n\n\n
\n\n\n\n \n \n $\"Dissociating$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{4415133,\n  abstract     = {{Acting in an uncertain environment requires estimating the probability and the value of potential outcomes. These computations are typically ascribed to various parts of the medial prefrontal cortex (mPFC), but the functional architecture of this region remains debated. The anterior cingulate cortex (ACC) encodes reward prediction and outcome (i.e. win vs lose, Silvetti, Seurinck, & Verguts, 2013. Cortex, 49(6), 1627-35. doi:10.1016/j.cortex.2012.05.008). An outcome-related value signal has also been reported in the ventromedial Prefrontal Cortex (vmPFC, Rangel & Hare, 2010. Current Opinion in Neurobiology, 20(2), 262-70. doi:10.1016/j.conb.2010.03.001). Whether a functional dissociation can be traced in these regions with respect to reward prediction and outcome has been suggested but not rigorously tested. Hence an fMRI study was designed to systematically examine the contribution of ACC and vmPFC to reward prediction and outcome. A striking dissociation was identified, with ACC coding for positive prediction errors and vmPFC responding to outcome, irrespective of probability. Moreover, ACC has been assigned a crucial role in the selection of intentional actions (decision-making) and computing the value associated to these actions (action-based value). Conversely, vmPFC seems to implement stimulus-based value processing (Rudebeck et al., 2008. Journal of Neuroscience, 28(51), 13775-85. doi:10.1523/JNEUROSCI.3541-08.2008; Rushworth, Behrens, Rudebeck, & Walton, 2007. Trends in Cognitive Sciences, 11(4), 168-76. doi:10.1016/j.tics.2007.01.004). Therefore, a decision-making factor (choice vs. no choice condition) was also implemented in the present paradigm to distinguish stimulus-based versus action-based value coding in the mPFC during both decision and outcome phase. We found that vmPFC was more activated during the outcome phase in the no-choice than in the choice condition, potentially confirming the role of this area in stimulus-based (more than action-based) value processing.}},\n  author       = {{Vassena, Eliana and Krebs, Ruth and Silvetti, Massimo and Fias, Wim and Verguts, Tom}},\n  issn         = {{0028-3932}},\n  journal      = {{NEUROPSYCHOLOGIA}},\n  keywords     = {{Prediction error,Outcome,ACC,Value,Choice,vmPFC}},\n  language     = {{eng}},\n  pages        = {{112--123}},\n  title        = {{Dissociating contributions of ACC and vmPFC in reward prediction, outcome and choice}},\n  url          = {{http://doi.org/10.1016/j.neuropsychologia.2014.04.019}},\n  volume       = {{59}},\n  year         = {{2014}},\n}\n\n

\n

\n\n\n

\n Acting in an uncertain environment requires estimating the probability and the value of potential outcomes. These computations are typically ascribed to various parts of the medial prefrontal cortex (mPFC), but the functional architecture of this region remains debated. The anterior cingulate cortex (ACC) encodes reward prediction and outcome (i.e. win vs lose, Silvetti, Seurinck, & Verguts, 2013. Cortex, 49(6), 1627-35. doi:10.1016/j.cortex.2012.05.008). An outcome-related value signal has also been reported in the ventromedial Prefrontal Cortex (vmPFC, Rangel & Hare, 2010. Current Opinion in Neurobiology, 20(2), 262-70. doi:10.1016/j.conb.2010.03.001). Whether a functional dissociation can be traced in these regions with respect to reward prediction and outcome has been suggested but not rigorously tested. Hence an fMRI study was designed to systematically examine the contribution of ACC and vmPFC to reward prediction and outcome. A striking dissociation was identified, with ACC coding for positive prediction errors and vmPFC responding to outcome, irrespective of probability. Moreover, ACC has been assigned a crucial role in the selection of intentional actions (decision-making) and computing the value associated to these actions (action-based value). Conversely, vmPFC seems to implement stimulus-based value processing (Rudebeck et al., 2008. Journal of Neuroscience, 28(51), 13775-85. doi:10.1523/JNEUROSCI.3541-08.2008; Rushworth, Behrens, Rudebeck, & Walton, 2007. Trends in Cognitive Sciences, 11(4), 168-76. doi:10.1016/j.tics.2007.01.004). Therefore, a decision-making factor (choice vs. no choice condition) was also implemented in the present paradigm to distinguish stimulus-based versus action-based value coding in the mPFC during both decision and outcome phase. We found that vmPFC was more activated during the outcome phase in the no-choice than in the choice condition, potentially confirming the role of this area in stimulus-based (more than action-based) value processing.\n

\n\n\n

\n\n\n\n\n\n

\n

\n \n 2013\n \n \n (10)\n \n \n

\n

\n \n \n

\n \n\n \n \n \n \n \n \n Value and prediction error estimation account for volatility effects in ACC: a model-based fMRI study.\n \n \n \n \n\n\n \n Silvetti, Massimo; Seurinck, R.; and Verguts, T.\n\n\n \n\n\n\n CORTEX, 49(6): 1627–1635. 2013.\n \n\n\n\n
\n\n\n\n \n \n $\"Value$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{3098766,\n  author       = {{Silvetti, Massimo and Seurinck, Ruth and Verguts, Tom}},\n  issn         = {{0010-9452}},\n  journal      = {{CORTEX}},\n  keywords     = {{ATTENTION,LIKELIHOOD,ANTERIOR CINGULATE CORTEX,PREFRONTAL CORTEX,COGNITIVE CONTROL,BEHAVIOR,REPRESENTATION,PERFORMANCE,UNCERTAINTY,INFORMATION,Volatility,ACC,Reinforcement learning,Prediction error,Reward}},\n  language     = {{eng}},\n  number       = {{6}},\n  pages        = {{1627--1635}},\n  title        = {{Value and prediction error estimation account for volatility effects in ACC: a model-based fMRI study}},\n  url          = {{http://doi.org/10.1016/j.cortex.2012.05.008}},\n  volume       = {{49}},\n  year         = {{2013}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Blinking predicts enhanced cognitive control.\n \n \n \n \n\n\n \n van Bochove, Marlies; Van der Haegen, L.; Notebaert, W.; and Verguts, T.\n\n\n \n\n\n\n COGNITIVE AFFECTIVE & BEHAVIORAL NEUROSCIENCE, 13(2): 346–354. 2013.\n \n\n\n\n
\n\n\n\n \n \n $\"Blinking$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{3179729,\n  abstract     = {{Recent models have suggested an important role for neuromodulation in explaining trial-to-trial adaptations in cognitive control. The adaptation-by-binding model (Verguts & Notebaert, Psychological review, 115(2), 518-525, 2008), for instance, suggests that increased cognitive control in response to conflict (e.g., incongruent flanker stimulus) is the result of stronger binding of stimulus, action, and context representations, mediated by neuromodulators like dopamine (DA) and/or norepinephrine (NE). We presented a flanker task and used the Gratton effect (smaller congruency effect following incongruent trials) as an index of cognitive control. We investigated the Gratton effect in relation to eye blinks (DA related) and pupil dilation (NE related). The results for pupil dilation were not unequivocal, but eye blinks clearly modulated the Gratton effect: The Gratton effect was enhanced after a blink trial, relative to after a no-blink trial, even when controlling for correlated variables. The latter suggests an important role for DA in cognitive control on a trial-to-trial basis.}},\n  author       = {{van Bochove, Marlies and Van der Haegen, Lise and Notebaert, Wim and Verguts, Tom}},\n  issn         = {{1530-7026}},\n  journal      = {{COGNITIVE AFFECTIVE & BEHAVIORAL NEUROSCIENCE}},\n  keywords     = {{NORADRENERGIC LOCUS-COERULEUS,MONOAMINE-OXIDASE ACTIVITY,SPONTANEOUS EYEBLINK RATE,CONFLICT ADAPTATION,PREFRONTAL CORTEX,FEATURE-INTEGRATION,PARKINSONS-DISEASE,ADAPTIVE GAIN,DOPAMINE,MODULATION,Cognitive control,Dopamine,Norephinephrine}},\n  language     = {{eng}},\n  number       = {{2}},\n  pages        = {{346--354}},\n  title        = {{Blinking predicts enhanced cognitive control}},\n  url          = {{http://doi.org/10.3758/s13415-012-0138-2}},\n  volume       = {{13}},\n  year         = {{2013}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Opposite effects of working memory on subjective visibility and priming.\n \n \n \n \n\n\n \n De Loof, Esther; Verguts, T.; Fias, W.; and Van Opstal, F.\n\n\n \n\n\n\n JOURNAL OF EXPERIMENTAL PSYCHOLOGY-LEARNING MEMORY AND COGNITION, 39(6): 1959–1965. 2013.\n \n\n\n\n
\n\n\n\n \n \n $\"Opposite$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{3181319,\n  author       = {{De Loof, Esther and Verguts, Tom and Fias, Wim and Van Opstal, Filip}},\n  issn         = {{0278-7393}},\n  journal      = {{JOURNAL OF EXPERIMENTAL PSYCHOLOGY-LEARNING MEMORY AND COGNITION}},\n  keywords     = {{PREFRONTAL CORTEX,INHIBITION,VISUAL-PERCEPTION,cognitive control,priming,THRESHOLD,WORKSPACE,SELECTIVE ATTENTION,ACCESS,working memory,consciousness,LOAD,COMPATIBILITY,CONSCIOUSNESS}},\n  language     = {{eng}},\n  number       = {{6}},\n  pages        = {{1959--1965}},\n  title        = {{Opposite effects of working memory on subjective visibility and priming}},\n  url          = {{http://doi.org/10.1037/a0033093}},\n  volume       = {{39}},\n  year         = {{2013}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n Increased cognitive control during norepinephrine release through acute vagus nerve stimulation.\n \n \n \n\n\n \n van Bochove, Marlies; De Taeye, L.; Vonck, K.; Raedt, R.; Meurs, A.; Boon, P.; Dauwe, I.; Notebaert, W.; and Verguts, T.\n\n\n \n\n\n\n In JOURNAL OF COGNITIVE NEUROSCIENCE, volume 25, pages 246–246, 2013. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@inproceedings{3258927,\n  author       = {{van Bochove, Marlies and De Taeye, Leen and Vonck, Kristl and Raedt, Robrecht and Meurs, Alfred and Boon, Paul and Dauwe, Ine and Notebaert, Wim and Verguts, Tom}},\n  booktitle    = {{JOURNAL OF COGNITIVE NEUROSCIENCE}},\n  issn         = {{0898-929X}},\n  language     = {{eng}},\n  location     = {{San Francisco, CA, USA}},\n  number       = {{suppl.}},\n  pages        = {{246--246}},\n  title        = {{Increased cognitive control during norepinephrine release through acute vagus nerve stimulation}},\n  volume       = {{25}},\n  year         = {{2013}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Is there a generalized magnitude system in the brain? Behavioral, neuroimaging, and computational evidence.\n \n \n \n \n\n\n \n Van Opstal, Filip; and Verguts, T.\n\n\n \n\n\n\n 2013.\n \n\n\n\n
\n\n\n\n \n \n $\"Is$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@misc{4085694,\n  articleno    = {{435}},\n  author       = {{Van Opstal, Filip and Verguts, Tom}},\n  issn         = {{1664-1078}},\n  keywords     = {{NUMERICAL MAGNITUDE,SIZE,MODEL,QUANTITY,REPRESENTATION,TIME,SPACE,NUMBER,RESPONSE-SELECTION,PARIETAL CORTEX}},\n  language     = {{eng}},\n  pages        = {{435:1--435:3}},\n  series       = {{FRONTIERS IN PSYCHOLOGY}},\n  title        = {{Is there a generalized magnitude system in the brain? Behavioral, neuroimaging, and computational evidence}},\n  url          = {{http://doi.org/10.3389/fpsyg.2013.00435}},\n  volume       = {{4}},\n  year         = {{2013}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n Threshold for visual awareness is associated with striatal dopamine D2 receptor binding.\n \n \n \n\n\n \n Van Opstal, Filip; Verguts, T.; Van Laeken, N.; De Vos, F.; Goethals, I.; and Fias, W.\n\n\n \n\n\n\n In JOURNAL OF COGNITIVE NEUROSCIENCE, pages 264–264, 2013. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@inproceedings{4152347,\n  author       = {{Van Opstal, Filip and Verguts, Tom and Van Laeken, Nick and De Vos, Filip and Goethals, Ingeborg and Fias, Wim}},\n  booktitle    = {{JOURNAL OF COGNITIVE NEUROSCIENCE}},\n  issn         = {{0898-929X}},\n  language     = {{eng}},\n  location     = {{San Francisco, CA, USA}},\n  number       = {{suppl.}},\n  pages        = {{264--264}},\n  title        = {{Threshold for visual awareness is associated with striatal dopamine D2 receptor binding}},\n  year         = {{2013}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Deficient reinforcement learning in medial frontal cortex as a model of dopamine-related motivational deficits in ADHD.\n \n \n \n \n\n\n \n Silvetti, Massimo; Wiersema, R.; Barke, E.; and Verguts, T.\n\n\n \n\n\n\n NEURAL NETWORKS, 46: 199–209. 2013.\n \n\n\n\n
\n\n\n\n \n \n $\"Deficient$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{4206979,\n  author       = {{Silvetti, Massimo and Wiersema, Roeljan and Barke, Edmund and Verguts, Tom}},\n  issn         = {{0893-6080}},\n  journal      = {{NEURAL NETWORKS}},\n  keywords     = {{ATTENTION-DEFICIT/HYPERACTIVITY DISORDER,ANTERIOR CINGULATE CORTEX,DUAL PATHWAY MODEL,ERROR-RELATED-NEGATIVITY,HYPERACTIVITY DISORDER,DECISION-MAKING,BASAL GANGLIA,REWARD ANTICIPATION,PREFRONTAL CORTEX,WORKING-MEMORY,ADHD,ACC,Reinforcement learning,Dopamine,Prediction error,Reward expectation}},\n  language     = {{eng}},\n  pages        = {{199--209}},\n  title        = {{Deficient reinforcement learning in medial frontal cortex as a model of dopamine-related motivational deficits in ADHD}},\n  url          = {{http://doi.org/10.1016/j.neunet.2013.05.008}},\n  volume       = {{46}},\n  year         = {{2013}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Disentangling conscious and unconscious processing: a subjective trial-based assessment approach.\n \n \n \n \n\n\n \n Van den Bussche, Eva; Vermeiren, A.; Desender, K.; Gevers, W.; Hughes, G.; Verguts, T.; and Reynvoet, B.\n\n\n \n\n\n\n FRONTIERS IN HUMAN NEUROSCIENCE, 7: 8. 2013.\n \n\n\n\n
\n\n\n\n \n \n $\"Disentangling$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{4211277,\n  abstract     = {{The most common method for assessing similarities and differences between conscious and unconscious processing is to compare the effects of unconscious (perceptually weak) stimuli, with conscious (perceptually strong) stimuli. Awareness of these stimuli is then assessed by objective performance on prime identification tasks. While this approach has proven extremely fruitful in furthering our understanding of unconscious cognition, it also suffers from some critical problems. We present an alternative methodology for comparing conscious and unconscious cognition. We used a priming version of a Stroop paradigm and after each trial, participants gave a subjective rating of the degree to which they were aware of the prime. Based on this trial-by-trial awareness assessment, conscious, uncertain, and unconscious trials were separated. Crucially, in all these conditions, the primes have identical perceptual strength. Significant priming was observed for all conditions, but the effects for conscious trials were significantly stronger, and no difference was observed between uncertain and unconscious trials. Thus, awareness of the prime has a large impact on congruency effects, even when signal strength is controlled for.}},\n  articleno    = {{769}},\n  author       = {{Van den Bussche, Eva and Vermeiren, Astrid and Desender, Kobe and Gevers, Wim and Hughes, Gethin and Verguts, Tom and Reynvoet, Bert}},\n  issn         = {{1662-5161}},\n  journal      = {{FRONTIERS IN HUMAN NEUROSCIENCE}},\n  keywords     = {{stimulus strength,prime awareness,unconscious processing,conscious processing,EXPERIENCE,BLINDSIGHT,PERCEPTION,INTROSPECTION,DISCRIMINATION,PRIME,TASK,AWARENESS,METACONTRAST MASKING,STIMULUS-RESPONSE,awareness assessment}},\n  language     = {{eng}},\n  pages        = {{8}},\n  title        = {{Disentangling conscious and unconscious processing: a subjective trial-based assessment approach}},\n  url          = {{http://doi.org/10.3389/fnhum.2013.00769}},\n  volume       = {{7}},\n  year         = {{2013}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Spontaneous summation or numerosity-selective coding?.\n \n \n \n \n\n\n \n Chen, Qi; and Verguts, T.\n\n\n \n\n\n\n 2013.\n \n\n\n\n
\n\n\n\n \n \n $\"Spontaneous$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@misc{4212831,\n  articleno    = {{886}},\n  author       = {{Chen, Qi and Verguts, Tom}},\n  issn         = {{1662-5161}},\n  keywords     = {{REPRESENTATION,NUMBER,PREFRONTAL CORTEX,MODEL,QUANTITIES,MONKEY,SENSE. numerical cognition,computational modeling,single-unit recording}},\n  language     = {{eng}},\n  series       = {{FRONTIERS IN HUMAN NEUROSCIENCE}},\n  title        = {{Spontaneous summation or numerosity-selective coding?}},\n  url          = {{http://doi.org/10.3389/fnhum.2013.00886}},\n  volume       = {{7}},\n  year         = {{2013}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n The influence of the noradrenergic system on optimal control of neural plasticity.\n \n \n \n \n\n\n \n Silvetti, Massimo; Seurinck, R.; van Bochove, M.; and Verguts, T.\n\n\n \n\n\n\n FRONTIERS IN BEHAVIORAL NEUROSCIENCE, 7. 2013.\n \n\n\n\n
\n\n\n\n \n \n $\"The$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{4227278,\n  abstract     = {{Decision making under uncertainty is challenging for any autonomous agent. The challenge increases when the environment’s stochastic properties change over time, i.e., when the environment is volatile. In order to efficiently adapt to volatile environments, agents must primarily rely on recent outcomes to quickly change their decision strategies; in other words, they need to increase their knowledge plasticity. On the contrary, in stable environments, knowledge stability must be preferred to preserve useful information against noise. Here we propose that in mammalian brain, the locus coeruleus (LC) is one of the nuclei involved in volatility estimation and in the subsequent control of neural plasticity. During a reinforcement learning task, LC activation, measured by means of pupil diameter, coded both for environmental volatility and learning rate. We hypothesize that LC could be responsible, through norepinephrinic modulation, for adaptations to optimize decision making in volatile environments. We also suggest a computational model on the interaction between the anterior cingulate cortex (ACC) and LC for volatility estimation.}},\n  articleno    = {{160}},\n  author       = {{Silvetti, Massimo and Seurinck, Ruth and van Bochove, Marlies and Verguts, Tom}},\n  issn         = {{1662-5153}},\n  journal      = {{FRONTIERS IN BEHAVIORAL NEUROSCIENCE}},\n  keywords     = {{AROUSAL,DYNAMICS,NEUROMODULATION,BRAIN-STEM,ADAPTIVE GAIN,PREFRONTAL CORTEX,OPTIMAL PERFORMANCE,LOCUS-COERULEUS,NEURONS,CAT,locus coeruleus,ACC,norepinephrine,plasticity,volatility,reinforcement learning,prediction error,learning rate}},\n  language     = {{eng}},\n  title        = {{The influence of the noradrenergic system on optimal control of neural plasticity}},\n  url          = {{http://doi.org/10.3389/fnbeh.2013.00160}},\n  volume       = {{7}},\n  year         = {{2013}},\n}\n\n

\n

\n\n\n\n\n\n

\n

\n \n 2012\n \n \n (7)\n \n \n

\n

\n \n \n

\n \n\n \n \n \n \n \n \n Reward modulates adaptations to conflict.\n \n \n \n \n\n\n \n Braem, Senne; Verguts, T.; Roggeman, C.; and Notebaert, W.\n\n\n \n\n\n\n COGNITION, 125(2): 324–332. 2012.\n \n\n\n\n
\n\n\n\n \n \n $\"Reward$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{2998788,\n  author       = {{Braem, Senne and Verguts, Tom and Roggeman, Chantal and Notebaert, Wim}},\n  issn         = {{0010-0277}},\n  journal      = {{COGNITION}},\n  keywords     = {{Task-switching,Conflict,Cognitive control,Reinforcement learning,RESPONSES,ASSOCIATIONS,Reward,ACTIVATION,TASK,ANTERIOR CINGULATE,PARKINSONS-DISEASE,COGNITIVE CONTROL,INDIVIDUAL-DIFFERENCES,BEHAVIORAL-INHIBITION,FEATURE-INTEGRATION}},\n  language     = {{eng}},\n  number       = {{2}},\n  pages        = {{324--332}},\n  title        = {{Reward modulates adaptations to conflict}},\n  url          = {{http://doi.org/10.1016/j.cognition.2012.07.015}},\n  volume       = {{125}},\n  year         = {{2012}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Word and deed: a computational model of instruction following.\n \n \n \n \n\n\n \n Ramamoorthy, Anand; and Verguts, T.\n\n\n \n\n\n\n BRAIN RESEARCH, 1439: 54–65. 2012.\n \n\n\n\n
\n\n\n\n \n \n $\"Word$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{3035863,\n  author       = {{Ramamoorthy, Anand and Verguts, Tom}},\n  issn         = {{0006-8993}},\n  journal      = {{BRAIN RESEARCH}},\n  keywords     = {{COGNITIVE CONTROL,SHORT-TERM-MEMORY,BASAL GANGLIA,HUMAN BRAIN,COMPREHENSION,ASSOCIATIONS,PLACEBO,SYSTEMS,NEUROPHYSIOLOGY,INVOLVEMENT,Hebbian learning,Prefrontal cortex,Basal ganglia,Instruction}},\n  language     = {{eng}},\n  pages        = {{54--65}},\n  title        = {{Word and deed: a computational model of instruction following}},\n  url          = {{http://doi.org/10.1016/j.brainres.2011.12.025}},\n  volume       = {{1439}},\n  year         = {{2012}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Cognitive and affective control.\n \n \n \n \n\n\n \n Pourtois, Gilles; Notebaert, W.; and Verguts, T.\n\n\n \n\n\n\n 2012.\n \n\n\n\n
\n\n\n\n \n \n $\"Cognitive$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@misc{3049886,\n  articleno    = {{473}},\n  author       = {{Pourtois, Gilles and Notebaert, Wim and Verguts, Tom}},\n  issn         = {{1664-1078}},\n  language     = {{eng}},\n  pages        = {{2}},\n  series       = {{FRONTIERS IN PSYCHOLOGY}},\n  title        = {{Cognitive and affective control}},\n  url          = {{http://doi.org/10.3389/fpsyg.2012.00477}},\n  volume       = {{3}},\n  year         = {{2012}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Computational models of human learning.\n \n \n \n \n\n\n \n Verguts, Tom\n\n\n \n\n\n\n In Seel, Norbert M, editor(s), Encyclopedia of the sciences of learning, pages 707–710. Springer, 2012.\n \n\n\n\n
\n\n\n\n \n \n $\"Computational$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@incollection{3097689,\n  author       = {{Verguts, Tom}},\n  booktitle    = {{Encyclopedia of the sciences of learning}},\n  editor       = {{Seel, Norbert M}},\n  isbn         = {{9781441914279}},\n  language     = {{eng}},\n  pages        = {{707--710}},\n  publisher    = {{Springer}},\n  title        = {{Computational models of human learning}},\n  url          = {{http://doi.org/10.1007/978-1-4419-1428-6_417}},\n  year         = {{2012}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Increasing set size breaks down sequential congruency: evidence for an associative locus of cognitive control.\n \n \n \n \n\n\n \n Blais, Chris; and Verguts, T.\n\n\n \n\n\n\n ACTA PSYCHOLOGICA, 141(2): 133–139. 2012.\n \n\n\n\n
\n\n\n\n \n \n $\"Increasing$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{3097718,\n  author       = {{Blais, Chris and Verguts, Tom}},\n  issn         = {{0001-6918}},\n  journal      = {{ACTA PSYCHOLOGICA}},\n  keywords     = {{CONFLICT ADAPTATION,PROPORTION CONGRUENT,FEATURE-INTEGRATION,AUTOMATIC PROCESSES,ANTERIOR CINGULATE,SIMON TASK,ADJUSTMENTS,CONTINGENCY,ACCOUNT,Cognitive control,Associative learning,Computational modeling}},\n  language     = {{eng}},\n  number       = {{2}},\n  pages        = {{133--139}},\n  title        = {{Increasing set size breaks down sequential congruency: evidence for an associative locus of cognitive control}},\n  url          = {{http://doi.org/10.1016/j.actpsy.2012.07.009}},\n  volume       = {{141}},\n  year         = {{2012}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Spatial intuition in elementary arithmetic : a neurocomputational account.\n \n \n \n \n\n\n \n Chen, Qi; and Verguts, T.\n\n\n \n\n\n\n PLOS ONE, 7(2): 8. 2012.\n \n\n\n\n
\n\n\n\n \n \n $\"Spatial$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{3097831,\n  abstract     = {{Elementary arithmetic (e. g., addition, subtraction) in humans has been shown to exhibit spatial properties. Its exact nature has remained elusive, however. To address this issue, we combine two earlier models for parietal cortex: A model we recently proposed on number-space interactions and a modeling framework of parietal cortex that implements radial basis functions for performing spatial transformations. Together, they provide us with a framework in which elementary arithmetic is based on evolutionarily more basic spatial transformations, thus providing the first implemented instance of Dehaene and Cohen's recycling hypothesis.}},\n  articleno    = {{e31180}},\n  author       = {{Chen, Qi and Verguts, Tom}},\n  issn         = {{1932-6203}},\n  journal      = {{PLOS ONE}},\n  keywords     = {{OPERATIONAL MOMENTUM,MOVEMENTS,PERCEPTION,REPRESENTATIONS,NUMBER LINE,NUMERICAL ESTIMATION,PARIETAL CORTEX}},\n  language     = {{eng}},\n  number       = {{2}},\n  pages        = {{8}},\n  title        = {{Spatial intuition in elementary arithmetic : a neurocomputational account}},\n  url          = {{http://doi.org/10.1371/journal.pone.0031180}},\n  volume       = {{7}},\n  year         = {{2012}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n Reinforcement learning, high-level cognition, and the human brain.\n \n \n \n\n\n \n Silvetti, Massimo; and Verguts, T.\n\n\n \n\n\n\n In Bright, Peter, editor(s), Neuroimaging : cognitive and clinical neuroscience, pages 283–296. InTech, 2012.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@incollection{3099055,\n  author       = {{Silvetti, Massimo and Verguts, Tom}},\n  booktitle    = {{Neuroimaging : cognitive and clinical neuroscience}},\n  editor       = {{Bright, Peter}},\n  isbn         = {{9789535106067}},\n  language     = {{eng}},\n  pages        = {{283--296}},\n  publisher    = {{InTech}},\n  title        = {{Reinforcement learning, high-level cognition, and the human brain}},\n  year         = {{2012}},\n}\n\n

\n

\n\n\n\n

\n\n\n\n\n\n

\n

\n \n 2011\n \n \n (11)\n \n \n

\n

\n \n \n

\n \n\n \n \n \n \n \n \n The implementation of verbal instructions: an fMRI study.\n \n \n \n \n\n\n \n Hartstra, Egbert; Kühn, S.; Verguts, T.; and Brass, M.\n\n\n \n\n\n\n HUMAN BRAIN MAPPING, 32(11): 1811–1824. 2011.\n \n\n\n\n
\n\n\n\n \n \n $\"The$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{1104899,\n  author       = {{Hartstra, Egbert and Kühn, Simone and Verguts, Tom and Brass, Marcel}},\n  issn         = {{1065-9471}},\n  journal      = {{HUMAN BRAIN MAPPING}},\n  keywords     = {{COGNITIVE CONTROL,INFERIOR FRONTAL JUNCTION,ARBITRARY VISUOMOTOR ASSOCIATIONS,PARIETAL CORTEX,PREFRONTAL CORTEX,MOTOR PREPARATION,BROCAS AREA,TASK,REPRESENTATIONS,INVOLVEMENT,verbal instructions,fMRI,cognitive control,prefrontal cortex,IPS}},\n  language     = {{eng}},\n  number       = {{11}},\n  pages        = {{1811--1824}},\n  title        = {{The implementation of verbal instructions: an fMRI study}},\n  url          = {{http://doi.org/10.1002/hbm.21152}},\n  volume       = {{32}},\n  year         = {{2011}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n The origins of the numerical distance effect: the same-different task.\n \n \n \n \n\n\n \n Van Opstal, Filip; and Verguts, T.\n\n\n \n\n\n\n EUROPEAN JOURNAL OF COGNITIVE PSYCHOLOGY, 23(1): 112–120. 2011.\n \n\n\n\n
\n\n\n\n \n \n $\"The$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{1162270,\n  abstract     = {{One of the most frequently used markers in research on numerical cognition is the distance effect. Recently, we have suggested that a distance effect can have different origins depending on the experimental task. By dissociating the comparison distance effect from the priming distance effect we revealed the need to study the origin of this effect before drawing any conclusions from it (van Opstal, Gevers, de Moor, & Verguts, 2008). Because a distance effect in a same-different task is also commonly used to study number representations (e. g., Dehaene & Akhavein, 1995), the present study aimed at uncovering the origin of the effect in this task. Computational and empirical results indicate clearly that the distance effect in the same-different task originates from number representations rather than a decision process.}},\n  author       = {{Van Opstal, Filip and Verguts, Tom}},\n  issn         = {{0954-1446}},\n  journal      = {{EUROPEAN JOURNAL OF COGNITIVE PSYCHOLOGY}},\n  keywords     = {{SIZE,ACHIEVEMENT,MODEL,REPRESENTATION,NUMBER,INDIVIDUAL-DIFFERENCES,Representation,Numerical cognition,Distance effect,CORTEX,QUANTITY}},\n  language     = {{eng}},\n  number       = {{1}},\n  pages        = {{112--120}},\n  title        = {{The origins of the numerical distance effect: the same-different task}},\n  url          = {{http://doi.org/10.1080/20445911.2011.466796}},\n  volume       = {{23}},\n  year         = {{2011}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n The size congruity effect: is bigger always more?.\n \n \n \n \n\n\n \n Santens, Seppe; and Verguts, T.\n\n\n \n\n\n\n COGNITION, 118(1): 94–110. 2011.\n \n\n\n\n
\n\n\n\n \n \n $\"The$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{1186857,\n  author       = {{Santens, Seppe and Verguts, Tom}},\n  issn         = {{0010-0277}},\n  journal      = {{COGNITION}},\n  keywords     = {{EVENT-RELATED FMRI,COMPARATIVE JUDGMENTS,COMPUTATIONAL MODEL,PARIETAL CORTEX,NUMBER,REPRESENTATION,MAGNITUDE,STROOP,INTERFERENCE,COMMON,Size congruity,Numerical Stroop,Numerical cognition,Number processing}},\n  language     = {{eng}},\n  number       = {{1}},\n  pages        = {{94--110}},\n  title        = {{The size congruity effect: is bigger always more?}},\n  url          = {{http://doi.org/10.1016/j.cognition.2010.10.014}},\n  volume       = {{118}},\n  year         = {{2011}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Stages of nonsymbolic number processing in occipitoparietal cortex disentangled by fMRI adaptation.\n \n \n \n \n\n\n \n Roggeman, Chantal; Santens, S.; Fias, W.; and Verguts, T.\n\n\n \n\n\n\n JOURNAL OF NEUROSCIENCE, 31(19): 7168–7173. 2011.\n \n\n\n\n
\n\n\n\n \n \n $\"Stages$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{1246279,\n  abstract     = {{The neurobiological mechanisms of nonsymbolic number processing in humans are still unclear. Computational modeling proposed three successive stages: first, the spatial location of objects is stored in an object location map; second, this information is transformed into a numerical summation code; third, this summation code is transformed to a number-selective code. Here, we used fMRI-adaptation to identify these three stages and their relative anatomical location. By presenting the same number of dots on the same locations in the visual field, we adapted neurons of human volunteers. Occasionally, deviants with the same number of dots at different locations or different numbers of dots at the same location were shown. By orthogonal number and location factors in the deviants, we were able to calculate three independent contrasts, each sensitive to one of the stages. We found an occipitoparietal gradient for nonsymbolic number processing: the activation of the object location map was found in the inferior occipital gyrus. The summation coding map exhibited a nonlinear pattern of activation, with first increasing and then decreasing activation, and most activity in the middle occipital gyrus. Finally, the number-selective code became more pronounced in the superior parietal lobe. In summary, we disentangled the three stages of nonsymbolic number processing predicted by computational modeling and demonstrated that they constitute a pathway along the occipitoparietal processing stream.}},\n  author       = {{Roggeman, Chantal and Santens, Seppe and Fias, Wim and Verguts, Tom}},\n  issn         = {{0270-6474}},\n  journal      = {{JOURNAL OF NEUROSCIENCE}},\n  keywords     = {{REPRESENTATIONS,MODEL,POSTERIOR PARIETAL CORTEX,SACCADES,MEMORY,MONKEY,QUANTITIES}},\n  language     = {{eng}},\n  number       = {{19}},\n  pages        = {{7168--7173}},\n  title        = {{Stages of nonsymbolic number processing in occipitoparietal cortex disentangled by fMRI adaptation}},\n  url          = {{http://doi.org/10.1523/JNEUROSCI.4503-10.2011}},\n  volume       = {{31}},\n  year         = {{2011}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Setting the stage subliminally: unconscious context effects.\n \n \n \n \n\n\n \n Van Opstal, Filip; Calderon, C.; Gevers, W.; and Verguts, T.\n\n\n \n\n\n\n CONSCIOUSNESS AND COGNITION, 20(4): 1860–1864. 2011.\n \n\n\n\n
\n\n\n\n \n \n $\"Setting$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{1897207,\n  author       = {{Van Opstal, Filip and Calderon, Cristian and Gevers, Wim and Verguts, Tom}},\n  issn         = {{1053-8100}},\n  journal      = {{CONSCIOUSNESS AND COGNITION}},\n  keywords     = {{MULTIPLE LEVELS,NAMING TASK,PROPORTION,ACTIVATION,DECISIONS,AWARENESS,JUDGMENT,CORTEX,Top-down,Subliminal priming,Context effects}},\n  language     = {{eng}},\n  number       = {{4}},\n  pages        = {{1860--1864}},\n  title        = {{Setting the stage subliminally: unconscious context effects}},\n  url          = {{http://doi.org/10.1016/j.concog.2011.09.004}},\n  volume       = {{20}},\n  year         = {{2011}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Conflict adaptation by means of associative learning.\n \n \n \n \n\n\n \n Braem, Senne; Verguts, T.; and Notebaert, W.\n\n\n \n\n\n\n JOURNAL OF EXPERIMENTAL PSYCHOLOGY: HUMAN PERCEPTION AND PERFORMANCE, 37(5): 1662–1666. 2011.\n \n\n\n\n
\n\n\n\n \n \n $\"Conflict$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{1929678,\n  abstract     = {{Cognitive control is responsible for adapting information processing in order to carry out tasks more efficiently. Contrasting global versus local control accounts, it has recently been proposed that control operates in an associative fashion, that is, by binding stimulus–response associations after detection of conflict (Verguts & Notebaert, 2009). Here, this prediction is explicitly tested for the first time. In a task-switching study where both tasks use the same relevant information, we previously reported conflict adaptation over tasks (Notebaert & Verguts, 2008). In the current experiment, we demonstrate that this is restricted to conditions where both tasks use the same effectors, thereby supporting the associative control account.}},\n  author       = {{Braem, Senne and Verguts, Tom and Notebaert, Wim}},\n  issn         = {{0096-1523}},\n  journal      = {{JOURNAL OF EXPERIMENTAL PSYCHOLOGY: HUMAN PERCEPTION AND PERFORMANCE}},\n  keywords     = {{COGNITIVE CONTROL,ITEM-SPECIFIC CONTROL,associative learning,task structure,cognitive control,CONTROL MECHANISMS,SIMON TASK,ADJUSTMENTS,INFORMATION,ACTIVATION,LOCATION}},\n  language     = {{eng}},\n  number       = {{5}},\n  pages        = {{1662--1666}},\n  title        = {{Conflict adaptation by means of associative learning}},\n  url          = {{http://doi.org/10.1037/a0024385}},\n  volume       = {{37}},\n  year         = {{2011}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Distance in motion: response trajectories reveal the dynamics of number comparison.\n \n \n \n \n\n\n \n Santens, Seppe; Goossens, S.; and Verguts, T.\n\n\n \n\n\n\n PLOS ONE, 6(9): 6. 2011.\n \n\n\n\n
\n\n\n\n \n \n $\"Distance$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{1935306,\n  abstract     = {{Cognitive and neuroscientific evidence has challenged the widespread view that perception, cognition and action constitute independent, discrete stages. For example, in continuous response trajectories toward a target response location, evidence suggests that a decision on which target to reach for (i.e., the cognition stage) is not reached before the movement starts (i.e., the action stage). As a result, instead of a straight trajectory to the correct target response, movement trajectories may curve toward competing responses or away from inhibited responses. In the present study, we examined response trajectories during a number comparison task. Participants had to decide whether a target number was smaller or larger than 5. They had to respond by moving to a left or a right response location. Replicating previous results, response trajectories were more curved toward the incorrect response location when distance to 5 was small (e. g., target number 4) than when distance to 5 was large (e. g., target number 1). Importantly, we manipulated the response mapping, which allowed us to demonstrate that this response trajectory effect results from the relative amount of evidence for the available responses across time. In this way, the present study stresses the tight coupling of number representations (i.e., cognition) and response related processes (i.e., action) and shows that these stages are not separable in time.}},\n  articleno    = {{e25429}},\n  author       = {{Santens, Seppe and Goossens, Sofie and Verguts, Tom}},\n  issn         = {{1932-6203}},\n  journal      = {{PLOS ONE}},\n  keywords     = {{REPRESENTATION,SPACE,MODEL}},\n  language     = {{eng}},\n  number       = {{9}},\n  pages        = {{6}},\n  title        = {{Distance in motion: response trajectories reveal the dynamics of number comparison}},\n  url          = {{http://doi.org/10.1371/journal.pone.0025429}},\n  volume       = {{6}},\n  year         = {{2011}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Post-conflict slowing: cognitive adaptation after conflict processing.\n \n \n \n \n\n\n \n Verguts, Tom; Notebaert, W.; Kunde, W.; and Wühr, P.\n\n\n \n\n\n\n PSYCHONOMIC BULLETIN & REVIEW, 18(1): 76–82. 2011.\n \n\n\n\n
\n\n\n\n \n \n $\"Post-conflict$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{1944008,\n  abstract     = {{The aftereffects of error and conflict (i.e., stimulus or response incongruency) have been extensively studied in the cognitive control literature. Each has been characterized by its own behavioral signature on the following trial. Conflict leads to a reduced congruency effect (Gratton effect), whereas an error leads to increased response time (post-error slowing). The reason for this dissociation has remained unclear. Here, we show that post-conflict slowing is not typically observed because it is masked by the processing of the irrelevant stimulus dimension. We demonstrate that post-conflict slowing does occur when tested in pure trials where helpful or detrimental impacts from irrelevant stimulus dimensions are removed (i.e., univalent stimuli).}},\n  author       = {{Verguts, Tom and Notebaert, Wim and Kunde, Wilfried and Wühr, Peter}},\n  issn         = {{1069-9384}},\n  journal      = {{PSYCHONOMIC BULLETIN & REVIEW}},\n  keywords     = {{Simon task,Cognitive control,Post-error slowing,TASK,ACCOUNT,ACTIVATION}},\n  language     = {{eng}},\n  number       = {{1}},\n  pages        = {{76--82}},\n  title        = {{Post-conflict slowing: cognitive adaptation after conflict processing}},\n  url          = {{http://doi.org/10.3758/s13423-010-0016-2}},\n  volume       = {{18}},\n  year         = {{2011}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Conflict and error adaptation in the Simon task.\n \n \n \n \n\n\n \n Notebaert, Wim; and Verguts, T.\n\n\n \n\n\n\n ACTA PSYCHOLOGICA, 136(2): 212–216. 2011.\n \n\n\n\n
\n\n\n\n \n \n $\"Conflict$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{1944023,\n  author       = {{Notebaert, Wim and Verguts, Tom}},\n  issn         = {{0001-6918}},\n  journal      = {{ACTA PSYCHOLOGICA}},\n  language     = {{eng}},\n  number       = {{2}},\n  pages        = {{212--216}},\n  title        = {{Conflict and error adaptation in the Simon task}},\n  url          = {{http://doi.org/10.1016/j.actpsy.2010.05.006}},\n  volume       = {{136}},\n  year         = {{2011}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Value and prediction error in medial frontal cortex: integrating the single-unit and systems levels of analysis.\n \n \n \n \n\n\n \n Silvetti, Massimo; Seurinck, R.; and Verguts, T.\n\n\n \n\n\n\n FRONTIERS IN HUMAN NEUROSCIENCE, 5: 15. 2011.\n \n\n\n\n
\n\n\n\n \n \n $\"Value$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{1989166,\n  abstract     = {{The role of the anterior cingulate cortex (ACC) in cognition has been extensively investigated with several techniques, including single-unit recordings in rodents and monkeys and EEG and fMRI in humans. This has generated a rich set of data and points of view. Important theoretical functions proposed for ACC are value estimation, error detection, error-likelihood estimation, conflict monitoring, and estimation of reward volatility. A unified view is lacking at this time, however. Here we propose that online value estimation could be the key function underlying these diverse data. This is instantiated in the reward value and prediction model (RVPM). The model contains units coding for the value of cues (stimuli or actions) and units coding for the differences between such values and the actual reward (prediction errors). We exposed the model to typical experimental paradigms from single-unit, EEG, and fMRI research to compare its overall behavior with the data from these studies. The model reproduced the ACC behavior of previous single-unit, EEG, and fMRI studies on reward processing, error processing, conflict monitoring, error-likelihood estimation, and volatility estimation, unifying the interpretations of the role performed by the ACC in some aspects of cognition.}},\n  articleno    = {{75}},\n  author       = {{Silvetti, Massimo and Seurinck, Ruth and Verguts, Tom}},\n  issn         = {{1662-5161}},\n  journal      = {{FRONTIERS IN HUMAN NEUROSCIENCE}},\n  keywords     = {{error likelihood,volatility,conflict monitoring,reinforcement learning,reward,dopamine,ACC,REWARD,CONFLICT,STROOP TASK,BASAL GANGLIA,FUNCTIONAL MRI,PREFRONTAL CORTEX,NEURAL REPRESENTATION,ANTERIOR CINGULATE CORTEX,ORBITOFRONTAL CORTEX,DOPAMINE NEURONS}},\n  language     = {{eng}},\n  pages        = {{15}},\n  title        = {{Value and prediction error in medial frontal cortex: integrating the single-unit and systems levels of analysis}},\n  url          = {{http://doi.org/10.3389/fnhum.2011.00075}},\n  volume       = {{5}},\n  year         = {{2011}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n Comparison of fMRI activation and EEG source localization using beamformers during motor response in the Stroop task: preliminary results.\n \n \n \n\n\n \n Strobbe, Gregor; Santens, S.; van Mierlo, P.; Hallez, H.; Van Opstal, F.; Rosseel, Y.; Verguts, T.; and Vandenberghe, S.\n\n\n \n\n\n\n In Proceedings of the 2011 8th International Symposium on Noninvasive Functional Source Imaging of the Brain and Heart and the 2011 8th International Conference on Bioelectromagnetism (NFSI and ICBEM), pages 98–102, 2011. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@inproceedings{3143423,\n  abstract     = {{The simultaneous measurement of neuro-functional MRI and EEG provides the opportunity to investigate both haemodynamic and electrical activity in the human brain non-invasively. This multimodal technique makes it possible to combine the advantages of EEG (millisecond temporal resolution) with those of fMRI (millimeter spatial accuracy). However, the combination of EEG and fMRI suffers also from their limitations: there is no clear relationship between neuronal activity, the EEG and the fMRI signals; mismatches are observed between EEG and fMRI analyses and there are experimental limitations. In this study we present a qualitative analysis of simultaneous acquired EEG/fMRI data from a single subject performing the Stroop task. The EEG data and the fMRI time series are processed separately focused on the motor responses. We apply a beamformer spatial filter to the EEG data to localize the electrical activity corresponding to the motor responses of the right and the left hand. The areas of maximum electrical activation are compared with the fMRI activation clusters. Both analyses show activation around the primary motor cortex. These results are an indication to start with a more sophisticated and integrated analysis of simultaneous acquired EEG/fMRI data during the Stroop task.}},\n  author       = {{Strobbe, Gregor and Santens, Seppe and van Mierlo, Pieter and Hallez, Hans and Van Opstal, Filip and Rosseel, Yves and Verguts, Tom and Vandenberghe, Stefaan}},\n  booktitle    = {{Proceedings of the 2011 8th International Symposium on Noninvasive Functional Source Imaging of the Brain and Heart and the 2011 8th International Conference on Bioelectromagnetism (NFSI and ICBEM)}},\n  isbn         = {{9781424482825}},\n  language     = {{eng}},\n  location     = {{Banff, Canada}},\n  pages        = {{98--102}},\n  title        = {{Comparison of fMRI activation and EEG source localization using beamformers during motor response in the Stroop task: preliminary results}},\n  year         = {{2011}},\n}\n\n

\n

\n\n\n\n\n\n

\n

\n \n 2010\n \n \n (7)\n \n \n

\n

\n \n \n

\n \n\n \n \n \n \n \n \n Number processing pathways in human parietal cortex.\n \n \n \n \n\n\n \n Santens, Seppe; Roggeman, C.; Fias, W.; and Verguts, T.\n\n\n \n\n\n\n CEREBRAL CORTEX, 20(1): 77–88. 2010.\n \n\n\n\n
\n\n\n\n \n \n $\"Number$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{622591,\n  abstract     = {{Numerous studies have identified the intraparietal sulcus (IPS) as an area critically involved in numerical processing. IPS neurons in macaques are tuned to a preferred numerosity, hence neurally coding numerosity in a number-selective way. Neuroimaging studies in humans have demonstrated number-selective processing in the anterior parts of the IPS. Nevertheless, the processes that convert visual input into a number-selective neural code remain unknown. Computational studies have suggested that a neural coding stage that is sensitive, but not selective to number, precedes number-selective coding when processing nonsymbolic quantities but not when processing symbolic quantities. In Experiment 1, we used functional magnetic resonance imaging to localize number-sensitive areas in the human brain by searching for areas exhibiting increasing activation with increasing number, carefully controlling for nonnumerical parameters. An area in posterior superior parietal cortex was identified as a substrate for the intermediate number-sensitive steps required for processing nonsymbolic quantities. In Experiment 2, the interpretation of Experiment 1 was confirmed with a connectivity analysis showing that a shared number-selective representation in IPS is reached through different pathways for symbolic versus nonsymbolic quantities. The preferred pathway for processing nonsymbolic quantities included the number-sensitive area in superior parietal cortex, whereas the pathway for processing symbolic quantities did not.}},\n  author       = {{Santens, Seppe and Roggeman, Chantal and Fias, Wim and Verguts, Tom}},\n  issn         = {{1047-3211}},\n  journal      = {{CEREBRAL CORTEX}},\n  keywords     = {{PRIMATE PREFRONTAL CORTEX,LATERAL INTRAPARIETAL AREA,EVENT-RELATED FMRI,NUMERICAL REPRESENTATIONS,CEREBRAL-CORTEX,MAGNITUDE,ATTENTION,BRAIN,CONNECTIVITY,PERCEPTION,fMRI,nonsymbolic,numerical cognition,numerical processing,symbolic}},\n  language     = {{eng}},\n  number       = {{1}},\n  pages        = {{77--88}},\n  title        = {{Number processing pathways in human parietal cortex}},\n  url          = {{http://doi.org/10.1093/cercor/bhp080}},\n  volume       = {{20}},\n  year         = {{2010}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Verbal-spatial and visuospatial coding of number-space interactions.\n \n \n \n \n\n\n \n Gevers, Wim; Santens, S.; D'Hooge, E.; Chen, Q.; Fias, W.; and Verguts, T.\n\n\n \n\n\n\n JOURNAL OF EXPERIMENTAL PSYCHOLOGY-GENERAL, 139(1): 180–190. 2010.\n \n\n\n\n
\n\n\n\n \n \n $\"Verbal-spatial$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{791119,\n  abstract     = {{A tight Correspondence has been postulated between the representation; of number and space The spatial numerical association of response codes (SNARC) effect. which reflects the observation that people. respond faster with the left-hand side to small numbers and with the right-hand side to large numbers. Is regarded as strong evidence for this correspondence The. dominant explanation of the SNARC effect a that it results from visuospatial coding of magnitude (e.g. the mental number line hypothesis) In a series of experiments, we demonstrated that this is only part of the story and that verbal-spatial coding influences processes and representations that have been believed to be. purely visuospatial Additionally, when both accounts were directly contrasted, verbal-spatial coding was observed in absence of visuospatial coding Relations to other number-space interactions and implications for other tasks are discussed}},\n  author       = {{Gevers, Wim and Santens, Seppe and D'Hooge, Elisah and Chen, Qi and Fias, Wim and Verguts, Tom}},\n  issn         = {{0096-3445}},\n  journal      = {{JOURNAL OF EXPERIMENTAL PSYCHOLOGY-GENERAL}},\n  keywords     = {{numerical cognition,SNARC effect,ASSOCIATION,MAGNITUDE,TASK,ATTENTION,LINE,SNARC,UNILATERAL NEGLECT,REPRESENTATIONAL SPACE,PICTURE-WORD INTERFERENCE,STIMULUS-RESPONSE COMPATIBILITY}},\n  language     = {{eng}},\n  number       = {{1}},\n  pages        = {{180--190}},\n  title        = {{Verbal-spatial and visuospatial coding of number-space interactions}},\n  url          = {{http://doi.org/10.1037/a0017688}},\n  volume       = {{139}},\n  year         = {{2010}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Beyond the mental number line: a neural network model of number-space interactions.\n \n \n \n \n\n\n \n Chen, Qi; and Verguts, T.\n\n\n \n\n\n\n COGNITIVE PSYCHOLOGY, 60(3): 218–240. 2010.\n \n\n\n\n
\n\n\n\n \n \n $\"Beyond$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{854350,\n  author       = {{Chen, Qi and Verguts, Tom}},\n  issn         = {{0010-0285}},\n  journal      = {{COGNITIVE PSYCHOLOGY}},\n  keywords     = {{SPLIT PROCESSING MODEL,PARIETAL CORTEX,UNILATERAL NEGLECT,SPATIAL REPRESENTATIONS,COGNITIVE MECHANISMS,NUMERICAL ABILITIES,PREFRONTAL CORTEX,FORM SYNAESTHESIA,Numerical cognition,Computational modeling,HUMAN INTRAPARIETAL CORTEX,VISUAL WORD RECOGNITION}},\n  language     = {{eng}},\n  number       = {{3}},\n  pages        = {{218--240}},\n  title        = {{Beyond the mental number line: a neural network model of number-space interactions}},\n  url          = {{http://doi.org/10.1016/j.cogpsych.2010.01.001}},\n  volume       = {{60}},\n  year         = {{2010}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Salience maps in parietal cortex : imaging and computational modeling.\n \n \n \n \n\n\n \n Roggeman, Chantal; Fias, W.; and Verguts, T.\n\n\n \n\n\n\n NEUROIMAGE, 52(3): 1005–1014. 2010.\n \n\n\n\n
\n\n\n\n \n \n $\"Salience$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{1096373,\n  author       = {{Roggeman, Chantal and Fias, Wim and Verguts, Tom}},\n  issn         = {{1053-8119}},\n  journal      = {{NEUROIMAGE}},\n  keywords     = {{LATERAL INTRAPARIETAL AREA,SHORT-TERM-MEMORY,VISUAL WORKING-MEMORY,INDIVIDUAL-DIFFERENCES,NEURAL MECHANISMS,FUNCTIONAL MRI,BRAIN ACTIVITY,ATTENTION,CAPACITY,FMRI}},\n  language     = {{eng}},\n  number       = {{3}},\n  pages        = {{1005--1014}},\n  title        = {{Salience maps in parietal cortex : imaging and computational modeling}},\n  url          = {{http://doi.org/10.1016/j.neuroimage.2010.01.060}},\n  volume       = {{52}},\n  year         = {{2010}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Geometric and featural representations in semantic concepts.\n \n \n \n \n\n\n \n Vanpaemel, Wolf; Verbeemen, T.; Dry, M.; Verguts, T.; and Storms, G.\n\n\n \n\n\n\n MEMORY & COGNITION, 38(7): 962–968. 2010.\n \n\n\n\n
\n\n\n\n \n \n $\"Geometric$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{1096387,\n  abstract     = {{We explore the adequacy of two types of similarity representation in the context of semantic concepts. To this end, we evaluate different categorization models, assuming either a geometric or a featural representation, using categorization decisions involving familiar and unfamiliar foods and animals. The study aims to assess the optimal stimulus representation as a function of the familiarity of the stimuli. For the unfamiliar stimuli, the geometric categorization models provide the best account of the categorization data, whereas for the familiar stimuli, the featural categorization models provide the best account. This pattern of results suggests that people rely on perceptual information to assign an unfamiliar stimulus to a category but rely on more elaborate conceptual knowledge when assigning a familiar stimulus.}},\n  author       = {{Vanpaemel, Wolf and Verbeemen, Timothy and Dry, Matthew and Verguts, Tom and Storms, Gert}},\n  issn         = {{0090-502X}},\n  journal      = {{MEMORY & COGNITION}},\n  keywords     = {{CONTEXT THEORY,MODEL,JUDGMENTS,COMPLEXITY,PROTOTYPES,SIMILARITY,CATEGORIZATION,STIMULUS,IDENTIFICATION,CLASSIFICATION}},\n  language     = {{eng}},\n  number       = {{7}},\n  pages        = {{962--968}},\n  title        = {{Geometric and featural representations in semantic concepts}},\n  url          = {{http://doi.org/10.3758/MC.38.7.962}},\n  volume       = {{38}},\n  year         = {{2010}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n Dyscalculie: getal-, taal-, en ruimte-interacties als basis van numerieke cognitie.\n \n \n \n\n\n \n Verguts, Tom; and Santens, S.\n\n\n \n\n\n\n LOGOPEDIE (HERENTALS), 23: 55–62. 2010.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{1096399,\n  abstract     = {{In de psychologie is de laatste tientallen jaren veel aandacht besteed aan de representatie en verwerking van getallen in het menselijke brein. Met name is benadrukt dat getallen in grote mate ‘spatiaal’ gerepresenteerd en verwerkt worden. Het geheel van onderzoeksresultaten wordt vaak samengevat door te stellen dat getallen gerepresenteerd worden op een ruimtelijk georiënteerde mentale getallenlijn. Recente bevindingen van onze onderzoeksgroep en daarbuiten hebben echter vraagtekens geplaatst bij het idee dat één structuur een verklaring kan bieden voor de vele bevindingen. In plaats daarvan vertrekken we van interacties tussen getalverwerking en ruimtelijke verwerking en tussen getalverwerking en taalverwerking. Wij geven hier een overzicht van de relevante literatuur en bespreken kort het nieuwe denkkader waarin de beschreven bevindingen geduid kunnen worden. Tot slot behandelen we de implicaties voor het begrijpen van dyscalculie.}},\n  author       = {{Verguts, Tom and Santens, Seppe}},\n  issn         = {{1370-706X}},\n  journal      = {{LOGOPEDIE (HERENTALS)}},\n  language     = {{dut}},\n  pages        = {{55--62}},\n  title        = {{Dyscalculie: getal-, taal-, en ruimte-interacties als basis van numerieke cognitie}},\n  volume       = {{23}},\n  year         = {{2010}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Unconscious task application.\n \n \n \n \n\n\n \n Van Opstal, Filip; Cevers, W.; Osman, M.; and Verguts, T.\n\n\n \n\n\n\n CONSCIOUSNESS AND COGNITION, 19(4): 999–1006. 2010.\n \n\n\n\n
\n\n\n\n \n \n $\"Unconscious$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

\n

@article{1096442,\n  author       = {{Van Opstal, Filip and Cevers, Wim and Osman, Magda and Verguts, Tom}},\n  issn         = {{1053-8100}},\n  journal      = {{CONSCIOUSNESS AND COGNITION}},\n  keywords     = {{KUNDE,MASKING}},\n  language     = {{eng}},\n  number       = {{4}},\n  pages        = {{999--1006}},\n  title        = {{Unconscious task application}},\n  url          = {{http://doi.org/10.1016/j.concog.2010.05.002}},\n  volume       = {{19}},\n  year         = {{2010}},\n}\n\n

\n

\n\n\n\n

\n\n\n\n\n\n

\n

\n \n 2009\n \n \n (6)\n \n \n

\n

\n \n \n

\n \n\n \n \n \n \n \n \n Post-error slowing: An orienting account.\n \n \n \n \n\n\n \n Notebaert, Wim; Houtman, F.; Van Opstal, F.; Gevers, W.; Fias, W.; and Verguts, T.\n\n\n \n\n\n\n COGNITION, 111(2): 275–279. 2009.\n \n\n\n\n
\n\n\n\n \n \n $\"Post-error$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{677702,\n  author       = {{Notebaert, Wim and Houtman, Femke and Van Opstal, Filip and Gevers, Wim and Fias, Wim and Verguts, Tom}},\n  issn         = {{0010-0277}},\n  journal      = {{COGNITION}},\n  keywords     = {{Cognitive control,Error monitoring,S-R COMPATIBILITY,ANTERIOR CINGULATE,COGNITIVE CONTROL,BRAIN POTENTIALS,ERP,NOVELTY,CORTEX,TASKS}},\n  language     = {{eng}},\n  number       = {{2}},\n  pages        = {{275--279}},\n  publisher    = {{Elsevier Science}},\n  title        = {{Post-error slowing: An orienting account}},\n  url          = {{http://doi.org/10.1016/j.cognition.2009.02.002}},\n  volume       = {{111}},\n  year         = {{2009}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n The neural representation of extensively trained ordered sequences.\n \n \n \n \n\n\n \n Van Opstal, Filip; Fias, W.; Peigneux, P.; and Verguts, T.\n\n\n \n\n\n\n NEUROIMAGE, 47(1): 367–375. 2009.\n \n\n\n\n
\n\n\n\n \n \n $\"The$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{698570,\n  abstract     = {{The role of the intraparietal sulcus (IPS) in number processing is largely agreed on. A current debate however concerns the specificity of the involvement of the IPS in representing numbers or ordinal sequences more generally. To test this specificity, we investigated whether the IPS would be activated by extensive training on an arbitrary ordered sequence. We found that the hippocampal-angular gyrus activation initially involved in learning the ordered sequences extends with extensive training to the left inferior frontal gyrus (left IFG), but not to the IPS. These results suggest that left IFG is a good candidate to process ordinal information, and that there is no need for an IPS area specifically dedicated to the representation of all ordinal sequences. Instead, we propose that the locus of the representation might be determined by the nature of the stimuli rather than its ordinal nature per se.}},\n  author       = {{Van Opstal, Filip and Fias, Wim and Peigneux, Philippe and Verguts, Tom}},\n  issn         = {{1053-8119}},\n  journal      = {{NEUROIMAGE}},\n  keywords     = {{ordinal sequences,inferior frontal gyrus,intraparietal sulcus,transitive inference}},\n  language     = {{eng}},\n  number       = {{1}},\n  pages        = {{367--375}},\n  title        = {{The neural representation of extensively trained ordered sequences}},\n  url          = {{http://doi.org/10.1016/j.neuroimage.2009.04.035}},\n  volume       = {{47}},\n  year         = {{2009}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Adaptation by binding: a learning account of cognitive control.\n \n \n \n \n\n\n \n Verguts, Tom; and Notebaert, W.\n\n\n \n\n\n\n TRENDS IN COGNITIVE SCIENCES, 13(6): 252–257. 2009.\n \n\n\n\n
\n\n\n\n \n \n $\"Adaptation$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{791026,\n  abstract     = {{Cognitive control refers to the ability to repress our instantaneous urges in favor of more appropriate responses. Current debate concerns whether cognitive control effects that are studied in the laboratory (e.g. Stroop tasks) actually reflect the operation of a cognitive control system (adaptation theory) or instead merely reflect side effects of feature binding processes (binding theory). The two perspectives can be integrated by conceptualizing cognitive control as resulting from interactions between binding processes (as instantiated in Hebbian learning) and arousal. Conflict situations such as Stroop incongruent-stimuli lead to arousal and noradrenalin release throughout the brain, which facilitates binding between task-relevant cortical areas. Our proposal emphasizes an intimate link between cognitive and emotional processing.}},\n  author       = {{Verguts, Tom and Notebaert, Wim}},\n  issn         = {{1364-6613}},\n  journal      = {{TRENDS IN COGNITIVE SCIENCES}},\n  keywords     = {{ANTERIOR CINGULATE,CONFLICT ADAPTATION,COMPUTATIONAL MODEL,AUTOMATIC PROCESSES,INTEGRATIVE THEORY,CONTROL MECHANISMS,CORTEX,TASK,ERROR,PERFORMANCE}},\n  language     = {{eng}},\n  number       = {{6}},\n  pages        = {{252--257}},\n  title        = {{Adaptation by binding: a learning account of cognitive control}},\n  url          = {{http://doi.org/10.1016/j.tics.2009.02.007}},\n  volume       = {{13}},\n  year         = {{2009}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Hippocampal involvement in the acquisition of relational associations, but not in the expression of a transitive inference task in mice.\n \n \n \n \n\n\n \n Van der Jeugd, Ann; Goddyn, H.; Laeremans, A.; Arckens, L.; D'Hooge, R.; and Verguts, T.\n\n\n \n\n\n\n BEHAVIORAL NEUROSCIENCE, 123(1): 109–114. 2009.\n \n\n\n\n
\n\n\n\n \n \n $\"Hippocampal$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{791031,\n  abstract     = {{The hippocampus (HC) has been suggested to play a role in transitive inference (TI) on an ordered sequence of stimuli. However, it has remained unclear whether HC is involved in the expression of TI, or rather contributes to TI through its role in the acquisition of the sequence of elements (Frank, Rudy, & O'Reilly, 2003). Presently, the authors compared the effects of excitotoxic dorsal HC lesions in C57BL mice that received surgery before or after they were trained to discriminate between pairs of visual stimuli. Performance on a subsequent TI task was worse in mice with pretraining lesions than in those with posttraining lesions, which showed similar performance to shams without lesions. This indicates that HC is not involved in the expression of TI, but may merely help to acquire the underlying representations required for TI.}},\n  author       = {{Van der Jeugd, Ann and Goddyn, Hannelore and Laeremans, Annelies and Arckens, Lutgarde and D'Hooge, Rudi and Verguts, Tom}},\n  issn         = {{0735-7044}},\n  journal      = {{BEHAVIORAL NEUROSCIENCE}},\n  keywords     = {{transitive inference,hippocampus,excitotoxic lesions,WORKING-MEMORY,LESIONS,AMNESIA,RATS,REPRESENTATION,ACTIVATION,NAVIGATION,HUMANS,MODEL}},\n  language     = {{eng}},\n  number       = {{1}},\n  pages        = {{109--114}},\n  title        = {{Hippocampal involvement in the acquisition of relational associations, but not in the expression of a transitive inference task in mice}},\n  url          = {{http://doi.org/10.1037/a0013990}},\n  volume       = {{123}},\n  year         = {{2009}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Abstract representations of number: what interactions with number form do not prove and priming effects do.\n \n \n \n \n\n\n \n Santens, Seppe; Fias, W.; and Verguts, T.\n\n\n \n\n\n\n 2009.\n \n\n\n\n
\n\n\n\n \n \n $\"Abstract$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

\n

@misc{791130,\n  abstract     = {{We challenge the arguments of Cohen Kadosh & Walsh (CK&W) on two grounds. First, interactions between number form (e.g., notation, format, modality) and an experimental factor do not show that the notations/formats/modalities are processed separately. Second, we discuss evidence that numbers are coded abstractly, also when riot required by task demands and processed unintentionally, thus challenging the authors' dual-code account}},\n  author       = {{Santens, Seppe and Fias, Wim and Verguts, Tom}},\n  issn         = {{0140-525X}},\n  keywords     = {{KUNDE,MODEL}},\n  language     = {{eng}},\n  number       = {{3-4}},\n  pages        = {{351--352}},\n  series       = {{BEHAVIORAL AND BRAIN SCIENCES}},\n  title        = {{Abstract representations of number: what interactions with number form do not prove and priming effects do}},\n  url          = {{http://doi.org/10.1017/S0140525X09990872}},\n  volume       = {{32}},\n  year         = {{2009}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Similarity and rules united: Similarity- and rule-based processing in a single neural network.\n \n \n \n \n\n\n \n Verguts, Tom; and Fias, W.\n\n\n \n\n\n\n Cognitive Science, 33(2): 243–259. 2009.\n \n\n\n\n
\n\n\n\n \n \n $\"Similarity$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{812867,\n  abstract     = {{A central controversy in cognitive science concerns the roles of rules versus similarity. To gain some leverage on this problem, we propose that rule- versus similarity-based processes can be characterized as extremes in a multidimensional space that is composed of at least two dimensions: the number of features (Pothos, 2005) and the physical presence of features. The transition of similarity- to rule-based processing is conceptualized as a transition in this space. To illustrate this, we show how a neural network model uses input features (and in this sense produces similarity-based responses) when it has a low learning rate or in the early phases of training, but it switches to using self-generated, more abstract features (and in this sense produces rule-based responses) when it has a higher learning rate or is in the later phases of training. Relations with categorization and the psychology of learning are pointed out.}},\n  author       = {{Verguts, Tom and Fias, Wim}},\n  issn         = {{0364-0213}},\n  journal      = {{Cognitive Science}},\n  keywords     = {{RATS,ANIMALS,BLOCKING,COGNITION,CONSTRAINTS,CATEGORIZATION,MODEL,CLASSIFICATION}},\n  language     = {{eng}},\n  number       = {{2}},\n  pages        = {{243--259}},\n  title        = {{Similarity and rules united: Similarity- and rule-based processing in a single neural network}},\n  url          = {{http://doi.org/10.1111/j.1551-6709.2009.01011.x}},\n  volume       = {{33}},\n  year         = {{2009}},\n}\n\n

\n

\n\n\n\n\n\n

\n

\n \n 2008\n \n \n (10)\n \n \n

\n

\n \n \n

\n \n\n \n \n \n \n \n A hippocampal - parietal network for learning an ordered sequence.\n \n \n \n\n\n \n Van Opstal, Filip; Verguts, T.; ORBAN, G.; and Fias, W.\n\n\n \n\n\n\n NEUROIMAGE, 40(1): 333–341. 2008.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{408518,\n  author       = {{Van Opstal, Filip and Verguts, Tom and ORBAN, GA and Fias, Wim}},\n  issn         = {{1053-8119}},\n  journal      = {{NEUROIMAGE}},\n  language     = {{eng}},\n  number       = {{1}},\n  pages        = {{333--341}},\n  title        = {{A hippocampal - parietal network for learning an ordered sequence}},\n  volume       = {{40}},\n  year         = {{2008}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n Offline and online automatic number comparison.\n \n \n \n\n\n \n Van Opstal, Filip; Moors, A.; Fias, W.; and Verguts, T.\n\n\n \n\n\n\n PSYCHOLOGICAL RESEARCH-PSYCHOLOGISCHE FORSCHUNG, 72(3): 347–352. 2008.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{408520,\n  author       = {{Van Opstal, Filip and Moors, Agnes and Fias, Wim and Verguts, Tom}},\n  issn         = {{0340-0727}},\n  journal      = {{PSYCHOLOGICAL RESEARCH-PSYCHOLOGISCHE FORSCHUNG}},\n  language     = {{eng}},\n  number       = {{3}},\n  pages        = {{347--352}},\n  title        = {{Offline and online automatic number comparison}},\n  volume       = {{72}},\n  year         = {{2008}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n A colorful walk, but is it on the mental number line? Reply to Cohen Kadosh, Tzelgov, and Henik.\n \n \n \n\n\n \n Verguts, Tom; and Van Opstal, F.\n\n\n \n\n\n\n 2008.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@misc{408522,\n  author       = {{Verguts, Tom and Van Opstal, Filip}},\n  issn         = {{0010-0277}},\n  language     = {{eng}},\n  number       = {{1}},\n  pages        = {{558--563}},\n  series       = {{COGNITION}},\n  title        = {{A colorful walk, but is it on the mental number line? Reply to Cohen Kadosh, Tzelgov, and Henik}},\n  volume       = {{106}},\n  year         = {{2008}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Hebbian learning of cognitive control: Dealing with specific and nonspecific adaptation.\n \n \n \n \n\n\n \n Verguts, Tom; and Notebaert, W.\n\n\n \n\n\n\n PSYCHOLOGICAL REVIEW, 115(2): 518–525. 2008.\n \n\n\n\n
\n\n\n\n \n \n $\"Hebbian$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{417731,\n  author       = {{Verguts, Tom and Notebaert, Wim}},\n  issn         = {{0033-295X}},\n  journal      = {{PSYCHOLOGICAL REVIEW}},\n  language     = {{eng}},\n  number       = {{2}},\n  pages        = {{518--525}},\n  title        = {{Hebbian learning of cognitive control: Dealing with specific and nonspecific adaptation}},\n  url          = {{https://osf.io/zzdbr/}},\n  volume       = {{115}},\n  year         = {{2008}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n Cognitive control acts locally.\n \n \n \n\n\n \n Notebaert, Wim; and Verguts, T.\n\n\n \n\n\n\n COGNITION, 106(2): 1071–1080. 2008.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{417765,\n  author       = {{Notebaert, Wim and Verguts, Tom}},\n  issn         = {{0010-0277}},\n  journal      = {{COGNITION}},\n  language     = {{eng}},\n  number       = {{2}},\n  pages        = {{1071--1080}},\n  title        = {{Cognitive control acts locally}},\n  volume       = {{106}},\n  year         = {{2008}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n Stimulus ambiguity elicits response conflict.\n \n \n \n\n\n \n Szmalec, Arnaud; Verbruggen, F.; Vandierendonck, A.; De Baene, W.; Verguts, T.; and Notebaert, W.\n\n\n \n\n\n\n NEUROSCIENCE LETTERS, 435(2): 158–162. 2008.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{433790,\n  author       = {{Szmalec, Arnaud and Verbruggen, Frederick and Vandierendonck, André and De Baene, Wouter and Verguts, Tom and Notebaert, Wim}},\n  issn         = {{0304-3940}},\n  journal      = {{NEUROSCIENCE LETTERS}},\n  language     = {{eng}},\n  number       = {{2}},\n  pages        = {{158--162}},\n  title        = {{Stimulus ambiguity elicits response conflict}},\n  volume       = {{435}},\n  year         = {{2008}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n Not all basic number representations are analog: place coding as a precursor of the natural number system.\n \n \n \n\n\n \n Fias, Wim; and Verguts, T.\n\n\n \n\n\n\n 2008.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@misc{539023,\n  author       = {{Fias, Wim and Verguts, Tom}},\n  issn         = {{0140-525X}},\n  language     = {{eng}},\n  number       = {{6}},\n  pages        = {{650--651}},\n  series       = {{BEHAVIORAL AND BRAIN SCIENCES}},\n  title        = {{Not all basic number representations are analog: place coding as a precursor of the natural number system}},\n  volume       = {{31}},\n  year         = {{2008}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Symbolic and nonsymbolic pathways of number processing.\n \n \n \n \n\n\n \n Verguts, Tom; and Fias, W.\n\n\n \n\n\n\n PHILOSOPHICAL PSYCHOLOGY, 21: 539–554. 2008.\n \n\n\n\n
\n\n\n\n \n \n $\"Symbolic$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{539034,\n  abstract     = {{Recent years have witnessed an enormous increase in behavioral and neuroimaging studies of numerical cognition. Particular interest has been devoted toward unraveling properties of the representational medium (mental number line) on which numbers are thought to be represented. We have argued that a correct inference concerning these properties requires distinguishing between different input modalities (symbolic vs. nonsymbolic stimuli; e.g., Verguts Fias, 2004) and different decision/output structures (task requirements; e.g., parity judgment task versus magnitude comparison task; Verguts, Fias, Stevens, 2005). To back up this claim, we have trained computational (neural network) models with either symbolic or nonsymbolic input and with different task requirements, and showed that this allowed for an integration of the existing data in a consistent manner. In later studies, predictions from the models were derived and tested with behavioral and neuroimaging methods. Here we present an integrative review of this work.}},\n  author       = {{Verguts, Tom and Fias, Wim}},\n  issn         = {{0951-5089}},\n  journal      = {{PHILOSOPHICAL PSYCHOLOGY}},\n  keywords     = {{numerical cognition,computational modelling,cognitive representations,REPRESENTATION,NEURAL BASIS,BRAIN-DAMAGE,HUMAN INFANTS,DIGIT NUMBERS,PARIETAL CORTEX,DECISION-MAKING,COMPUTATIONAL MODEL,MENTAL NUMBER,PREFRONTAL CORTEX,nonsymbolic number,symbolic number}},\n  language     = {{eng}},\n  pages        = {{539--554}},\n  title        = {{Symbolic and nonsymbolic pathways of number processing}},\n  url          = {{http://doi.org/10.1080/09515080802285545}},\n  volume       = {{21}},\n  year         = {{2008}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Dissecting the symbolic distance effect: comparison and priming effects in numerical and nonnumerical orders.\n \n \n \n \n\n\n \n Van Opstal, Filip; Gevers, W.; De Moor, W.; and Verguts, T.\n\n\n \n\n\n\n PSYCHONOMIC BULLETIN & REVIEW, 15(2): 419–425. 2008.\n \n\n\n\n
\n\n\n\n \n \n $\"Dissecting$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{539047,\n  abstract     = {{When participants are asked to compare two stimuli, responses are slower for stimuli close to each other on the relevant dimension than for stimuli further apart. Previously, it has been proposed that this comparison distance effect originates from overlap in the representation of the stimuli. This idea is generally accepted in numerical cognition, where it is assumed that representational overlap of numbers on a mental number line accounts for the effect (e.g., Cohen Kadosh et al., 2005). In contrast, others have emphasized the role of response-related processes to explain the comparison distance effect (e.g., Banks, 1977). In the present study, numbers and letters are used to show that the comparison distance effect can be dissociated from a more direct behavioral signature of representational overlap, the priming distance effect. The implication is that a comparison distance effect does riot imply representational overlap. An interpretation is given in terms of a recently proposed model of quantity comparison (Verguts, Fias, & Stevens, 2005).}},\n  author       = {{Van Opstal, Filip and Gevers, Wim and De Moor, Wendy and Verguts, Tom}},\n  issn         = {{1069-9384}},\n  journal      = {{PSYCHONOMIC BULLETIN & REVIEW}},\n  keywords     = {{NUMBERS,JUDGMENTS,NUMEROSITY,DISSOCIATION,MODEL,REPRESENTATION,FMRI}},\n  language     = {{eng}},\n  number       = {{2}},\n  pages        = {{419--425}},\n  title        = {{Dissecting the symbolic distance effect: comparison and priming effects in numerical and nonnumerical orders}},\n  url          = {{http://doi.org/10.3758/PBR.15.2.419}},\n  volume       = {{15}},\n  year         = {{2008}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Incidence of vaginal intraepithelial neoplasia after hysterectomy for cervical intraepithelial neoplasia: a retrospective study.\n \n \n \n \n\n\n \n Schokkaert, Silke; Poppe, W.; Arbyn, M.; Verguts, T.; and Verguts, J.\n\n\n \n\n\n\n AMERICAN JOURNAL OF OBSTETRICS AND GYNECOLOGY, 199(2). 2008.\n \n\n\n\n
\n\n\n\n \n \n $\"Incidence$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{594094,\n  abstract     = {{OBJECTIVE: Hysterectomy with concomitant cervical intraepithelial neoplasia (CIN), is often considered a definitive treatment for CIN, but development of subsequent vaginal intraepithelial neoplasia (VAIN) is known to range from 0.9% to 6.8%.\r\n\r\nSTUDY DESIGN: In a retrospective analysis of 3030 women with CIN2+ without history of VAIN in the University Hospital Gasthuisberg, Leuven, Belgium, from January 1989 until December 2003, we identified 125 women who underwent a hysterectomy within 6 months after diagnosis of CIN2+ and reviewed their postoperative Papanicolaou smears.\r\n\r\nRESULTS: Thirty-one patients (24.8%) were lost to follow-up. Seven of the 94 women in the follow-up group (7.4%) developed VAIN2+, of which 2 were invasive vaginal cancers. Median interval between hysterectomy and diagnosis of VAIN2+ was 35 months (5-103 months). Women with recurrence were significantly older (P = .003).\r\n\r\nCONCLUSION: Hysterectomy may not be considered as a definitive therapy for CIN2+ because the incidence rate of subsequent VAIN2+ is as high as 7.4%.}},\n  author       = {{Schokkaert, Silke and Poppe, Willy and Arbyn, Marc and Verguts, Tom and Verguts, Jasper}},\n  issn         = {{0002-9378}},\n  journal      = {{AMERICAN JOURNAL OF OBSTETRICS AND GYNECOLOGY}},\n  keywords     = {{MANAGEMENT,SQUAMOUS-CELL CARCINOMA,vaginal intraepithelial neoplasia,Papanicolaou smears,cervical intraepithelial neoplasia,hysterectomy,CANCER,CONIZATION,SMEARS,WOMEN,RISK}},\n  language     = {{eng}},\n  number       = {{2}},\n  publisher    = {{MOSBY-ELSEVIER}},\n  title        = {{Incidence of vaginal intraepithelial neoplasia after hysterectomy for cervical intraepithelial neoplasia: a retrospective study}},\n  url          = {{http://doi.org/10.1016/j.ajog.2008.02.026}},\n  volume       = {{199}},\n  year         = {{2008}},\n}\n\n

\n

\n\n\n\n\n\n

\n

\n \n 2007\n \n \n (6)\n \n \n

\n

\n \n \n

\n \n\n \n \n \n \n \n How to compare two quantities? A computational model of flutter discrimination.\n \n \n \n\n\n \n Verguts, Tom\n\n\n \n\n\n\n JOURNAL OF COGNITIVE NEUROSCIENCE, 19(3): 409–419. 2007.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{367864,\n  author       = {{Verguts, Tom}},\n  issn         = {{0898-929X}},\n  journal      = {{JOURNAL OF COGNITIVE NEUROSCIENCE}},\n  language     = {{eng}},\n  number       = {{3}},\n  pages        = {{409--419}},\n  publisher    = {{M I T PRESS}},\n  title        = {{How to compare two quantities? A computational model of flutter discrimination}},\n  volume       = {{19}},\n  year         = {{2007}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n Is masked neighbor priming inhibitory? Evidence using the incremental priming technique.\n \n \n \n\n\n \n De Moor, Wendy; Van der Herten, L.; and Verguts, T.\n\n\n \n\n\n\n EXPERIMENTAL PSYCHOLOGY, 54(2): 113–119. 2007.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{368912,\n  author       = {{De Moor, Wendy and Van der Herten, Liesbeth and Verguts, Tom}},\n  issn         = {{1618-3169}},\n  journal      = {{EXPERIMENTAL PSYCHOLOGY}},\n  language     = {{eng}},\n  number       = {{2}},\n  pages        = {{113--119}},\n  publisher    = {{HOGREFE & HUBER PUBLISHERS}},\n  title        = {{Is masked neighbor priming inhibitory? Evidence using the incremental priming technique}},\n  volume       = {{54}},\n  year         = {{2007}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n Priming reveals differential coding of symbolic and non-symbolic quantities.\n \n \n \n\n\n \n Roggeman, Chantal; Verguts, T.; and Fias, W.\n\n\n \n\n\n\n COGNITION, 105(2): 380–394. 2007.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{416360,\n  author       = {{Roggeman, Chantal and Verguts, Tom and Fias, Wim}},\n  issn         = {{0010-0277}},\n  journal      = {{COGNITION}},\n  language     = {{eng}},\n  number       = {{2}},\n  pages        = {{380--394}},\n  title        = {{Priming reveals differential coding of symbolic and non-symbolic quantities}},\n  volume       = {{105}},\n  year         = {{2007}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n Neighborhood consistency in mental arithmetic: Behavioral and ERP evidence.\n \n \n \n\n\n \n DOMAHS, F; DOMAHS, U; SCHLESEWSKY, M; Ratinckx, E.; Verguts, T.; WILLMES, K; and NUERK, H.\n\n\n \n\n\n\n BEHAVIORAL AND BRAIN FUNCTIONS, 3. 2007.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{417732,\n  author       = {{DOMAHS, F and DOMAHS, U and SCHLESEWSKY, M and Ratinckx, Elie and Verguts, Tom and WILLMES, K and NUERK, HC}},\n  issn         = {{1744-9081}},\n  journal      = {{BEHAVIORAL AND BRAIN FUNCTIONS}},\n  language     = {{eng}},\n  title        = {{Neighborhood consistency in mental arithmetic: Behavioral and ERP evidence}},\n  volume       = {{3}},\n  year         = {{2007}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n Dissociating conflict adaptation from feature integration: A multiple regression approach.\n \n \n \n\n\n \n Notebaert, Wim; and Verguts, T.\n\n\n \n\n\n\n Journal of experimental psychology. Human perception and performance, 33(5): 1256–1260. 2007.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{417768,\n  author       = {{Notebaert, Wim and Verguts, Tom}},\n  issn         = {{0096-1523}},\n  journal      = {{Journal of experimental psychology. Human perception and performance}},\n  language     = {{eng}},\n  number       = {{5}},\n  pages        = {{1256--1260}},\n  title        = {{Dissociating conflict adaptation from feature integration: A multiple regression approach}},\n  volume       = {{33}},\n  year         = {{2007}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n Beyond exemplars and prototypes as memory representations of natural concepts: A clustering approach.\n \n \n \n\n\n \n VERBEEMEN, T; VANPAEMEL, W; Pattyn, S.; STORMS, G; and Verguts, T.\n\n\n \n\n\n\n JOURNAL OF MEMORY AND LANGUAGE, 56(4): 537–554. 2007.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{417774,\n  author       = {{VERBEEMEN, T and VANPAEMEL, W and Pattyn, Sven and STORMS, G and Verguts, Tom}},\n  issn         = {{0749-596X}},\n  journal      = {{JOURNAL OF MEMORY AND LANGUAGE}},\n  language     = {{eng}},\n  number       = {{4}},\n  pages        = {{537--554}},\n  title        = {{Beyond exemplars and prototypes as memory representations of natural concepts: A clustering approach}},\n  volume       = {{56}},\n  year         = {{2007}},\n}\n\n

\n

\n\n\n\n

\n\n\n\n\n\n

\n

\n \n 2006\n \n \n (7)\n \n \n

\n

\n \n \n

\n \n\n \n \n \n \n \n Numbers and space: A computational model of the SNARC effect.\n \n \n \n\n\n \n Gevers, Wim; Verguts, T.; Reynvoet, B.; Caessens, B.; and Fias, W.\n\n\n \n\n\n\n Journal of experimental psychology. Human perception and performance, 32(1): 32–44. 2006.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{332853,\n  author       = {{Gevers, Wim and Verguts, Tom and Reynvoet, Bert and Caessens, Bernie and Fias, Wim}},\n  issn         = {{0096-1523}},\n  journal      = {{Journal of experimental psychology. Human perception and performance}},\n  language     = {{eng}},\n  number       = {{1}},\n  pages        = {{32--44}},\n  publisher    = {{AMER PSYCHOLOGICAL ASSOC/EDUCATIONAL PUBLISHING FOUNDATION}},\n  title        = {{Numbers and space: A computational model of the SNARC effect}},\n  volume       = {{32}},\n  year         = {{2006}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n The representation of multiplication facts: Developmental changes in the problem size, five, and tie effects.\n \n \n \n\n\n \n De Brauwer, Jolien; Verguts, T.; and Fias, W.\n\n\n \n\n\n\n JOURNAL OF EXPERIMENTAL CHILD PSYCHOLOGY, 94(1): 43–56. 2006.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{338902,\n  author       = {{De Brauwer, Jolien and Verguts, Tom and Fias, Wim}},\n  issn         = {{0022-0965}},\n  journal      = {{JOURNAL OF EXPERIMENTAL CHILD PSYCHOLOGY}},\n  language     = {{eng}},\n  number       = {{1}},\n  pages        = {{43--56}},\n  publisher    = {{ACADEMIC PRESS INC ELSEVIER SCIENCE}},\n  title        = {{The representation of multiplication facts: Developmental changes in the problem size, five, and tie effects}},\n  volume       = {{94}},\n  year         = {{2006}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n Shared spatial representations for numbers and space: The reversal of the SNARC and the Simon effects.\n \n \n \n\n\n \n Notebaert, Wim; Gevers, W.; Verguts, T.; and Fias, W.\n\n\n \n\n\n\n Journal of experimental psychology. Human perception and performance, 32(5): 1197–1207. 2006.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{366549,\n  author       = {{Notebaert, Wim and Gevers, Wim and Verguts, Tom and Fias, Wim}},\n  issn         = {{0096-1523}},\n  journal      = {{Journal of experimental psychology. Human perception and performance}},\n  language     = {{eng}},\n  number       = {{5}},\n  pages        = {{1197--1207}},\n  publisher    = {{AMER PSYCHOLOGICAL ASSOC/EDUCATIONAL PUBLISHING FOUNDATION}},\n  title        = {{Shared spatial representations for numbers and space: The reversal of the SNARC and the Simon effects}},\n  volume       = {{32}},\n  year         = {{2006}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n Stimulus conflict predicts conflict adaptation in a numerical flanker task.\n \n \n \n\n\n \n Notebaert, Wim; and Verguts, T.\n\n\n \n\n\n\n PSYCHONOMIC BULLETIN & REVIEW, 13(6): 1078–1084. 2006.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{367821,\n  author       = {{Notebaert, Wim and Verguts, Tom}},\n  issn         = {{1069-9384}},\n  journal      = {{PSYCHONOMIC BULLETIN & REVIEW}},\n  language     = {{eng}},\n  number       = {{6}},\n  pages        = {{1078--1084}},\n  publisher    = {{PSYCHONOMIC SOC INC}},\n  title        = {{Stimulus conflict predicts conflict adaptation in a numerical flanker task}},\n  volume       = {{13}},\n  year         = {{2006}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n When are neighbours hostile? Inhibitory neighbour effects in visual word recognition.\n \n \n \n\n\n \n De Moor, Wendy; and Verguts, T.\n\n\n \n\n\n\n PSYCHOLOGICAL RESEARCH-PSYCHOLOGISCHE FORSCHUNG, 70(5): 359–366. 2006.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{367860,\n  author       = {{De Moor, Wendy and Verguts, Tom}},\n  issn         = {{0340-0727}},\n  journal      = {{PSYCHOLOGICAL RESEARCH-PSYCHOLOGISCHE FORSCHUNG}},\n  language     = {{eng}},\n  number       = {{5}},\n  pages        = {{359--366}},\n  publisher    = {{Springer}},\n  title        = {{When are neighbours hostile? Inhibitory neighbour effects in visual word recognition}},\n  volume       = {{70}},\n  year         = {{2006}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n Lexical and syntactic structures in a connectionist model of reading multi-digit numbers.\n \n \n \n\n\n \n Verguts, Tom; and Fias, W.\n\n\n \n\n\n\n CONNECTION SCIENCE, 18(3): 265–285. 2006.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{367863,\n  author       = {{Verguts, Tom and Fias, Wim}},\n  issn         = {{0954-0091}},\n  journal      = {{CONNECTION SCIENCE}},\n  language     = {{eng}},\n  number       = {{3}},\n  pages        = {{265--285}},\n  publisher    = {{TAYLOR & FRANCIS LTD}},\n  title        = {{Lexical and syntactic structures in a connectionist model of reading multi-digit numbers}},\n  volume       = {{18}},\n  year         = {{2006}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Automatic response activation of implicit spatial information: Evidence from the SNARC effect.\n \n \n \n \n\n\n \n Gevers, Wim; Lammertyn, J.; Notebaert, W.; Verguts, T.; and Fias, W.\n\n\n \n\n\n\n ACTA PSYCHOLOGICA, 122(3): 221–233. 2006.\n \n\n\n\n
\n\n\n\n \n \n $\"Automatic$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{413128,\n  author       = {{Gevers, Wim and Lammertyn, Jan and Notebaert, Wim and Verguts, Tom and Fias, Wim}},\n  issn         = {{0001-6918}},\n  journal      = {{ACTA PSYCHOLOGICA}},\n  language     = {{eng}},\n  number       = {{3}},\n  pages        = {{221--233}},\n  publisher    = {{Elsevier Science}},\n  title        = {{Automatic response activation of implicit spatial information: Evidence from the SNARC effect}},\n  url          = {{http://doi.org/1854/7436}},\n  volume       = {{122}},\n  year         = {{2006}},\n}\n\n

\n

\n\n\n\n

\n\n\n\n\n\n

\n

\n \n 2005\n \n \n (8)\n \n \n

\n

\n \n \n

\n \n\n \n \n \n \n \n Interacting neighbors: A connectionist model of retrieval in single-digit multiplication.\n \n \n \n\n\n \n Verguts, Tom; and Fias, W.\n\n\n \n\n\n\n MEMORY & COGNITION, 33(1): 1–16. 2005.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{304098,\n  author       = {{Verguts, Tom and Fias, Wim}},\n  issn         = {{0090-502X}},\n  journal      = {{MEMORY & COGNITION}},\n  language     = {{eng}},\n  number       = {{1}},\n  pages        = {{1--16}},\n  publisher    = {{PSYCHONOMIC SOC INC}},\n  title        = {{Interacting neighbors: A connectionist model of retrieval in single-digit multiplication}},\n  volume       = {{33}},\n  year         = {{2005}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n A model of exact small-number representation.\n \n \n \n\n\n \n Verguts, Tom; Fias, W.; and Stevens, M.\n\n\n \n\n\n\n PSYCHONOMIC BULLETIN & REVIEW, 12(1): 66–80. 2005.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{315876,\n  author       = {{Verguts, Tom and Fias, Wim and Stevens, Michaël}},\n  issn         = {{1069-9384}},\n  journal      = {{PSYCHONOMIC BULLETIN & REVIEW}},\n  language     = {{eng}},\n  number       = {{1}},\n  pages        = {{66--80}},\n  publisher    = {{PSYCHONOMIC SOC INC}},\n  title        = {{A model of exact small-number representation}},\n  volume       = {{12}},\n  year         = {{2005}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n Neighbourhood effects in mental arithmetic.\n \n \n \n\n\n \n Verguts, Tom; and Fias, W.\n\n\n \n\n\n\n PSYCHOLOGY SCIENCE, 47(1): 132–140. 2005.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{331591,\n  author       = {{Verguts, Tom and Fias, Wim}},\n  issn         = {{1614-9947}},\n  journal      = {{PSYCHOLOGY SCIENCE}},\n  language     = {{eng}},\n  number       = {{1}},\n  pages        = {{132--140}},\n  title        = {{Neighbourhood effects in mental arithmetic}},\n  volume       = {{47}},\n  year         = {{2005}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n How to trigger elaborate processing? A comment on Kunde, Kiesel, and Hoffmann (2003).\n \n \n \n\n\n \n Van Opstal, Filip; REYNVOET, B; and Verguts, T.\n\n\n \n\n\n\n COGNITION, 97(1): 89–97. 2005.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{331604,\n  author       = {{Van Opstal, Filip and REYNVOET, B and Verguts, Tom}},\n  issn         = {{0010-0277}},\n  journal      = {{COGNITION}},\n  language     = {{eng}},\n  number       = {{1}},\n  pages        = {{89--97}},\n  publisher    = {{Elsevier Science}},\n  title        = {{How to trigger elaborate processing? A comment on Kunde, Kiesel, and Hoffmann (2003)}},\n  volume       = {{97}},\n  year         = {{2005}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n Unconscious semantic categorization and mask interactions: An elaborate response to Kunde et al. (2005).\n \n \n \n\n\n \n Van Opstal, Filip; REYNVOET, B; and Verguts, T.\n\n\n \n\n\n\n 2005.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@misc{331606,\n  author       = {{Van Opstal, Filip and REYNVOET, B and Verguts, Tom}},\n  issn         = {{0010-0277}},\n  language     = {{eng}},\n  number       = {{1}},\n  pages        = {{107--113}},\n  publisher    = {{Elsevier Science}},\n  series       = {{COGNITION}},\n  title        = {{Unconscious semantic categorization and mask interactions: An elaborate response to Kunde et al. (2005)}},\n  volume       = {{97}},\n  year         = {{2005}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Testing the Multiple in the multiple read-out model of visual word recognition.\n \n \n \n \n\n\n \n De Moor, Wendy; Verguts, T.; and Brysbaert, M.\n\n\n \n\n\n\n JOURNAL OF EXPERIMENTAL PSYCHOLOGY-LEARNING MEMORY AND COGNITION, 31(6): 1502–1508. 2005.\n \n\n\n\n
\n\n\n\n \n \n $\"Testing$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{332858,\n  abstract     = {{This study provided a test of the multiple criteria concept used for lexical decision, as implemented in J. Grainger and A. M. Jacobs's (1996) multiple read-out model. This account predicts more inhibition (or less facilitation) from a masked neighbor when accuracy is stressed more but more facilitation (or less inhibition) when the speed of responding is emphasized more. The authors tested these predictions by stressing accuracy (Experiment 1) and response speed (Experiment 2). The results of Experiment I showed a stronger neighbor-inhibition effect in the stress-on-accuracy condition than in the control condition. The results of Experiment 2 showed facilitation because of the neighbor prime in the stress-on-speed condition relative to the control condition. These results corroborate the multiple criteria account.}},\n  author       = {{De Moor, Wendy and Verguts, Tom and Brysbaert, Marc}},\n  issn         = {{0278-7393}},\n  journal      = {{JOURNAL OF EXPERIMENTAL PSYCHOLOGY-LEARNING MEMORY AND COGNITION}},\n  keywords     = {{visual word recognition,lexical decision,masked neighbor priming,multiple criteria account,multiple read-out model,AGE-OF-ACQUISITION,LEXICAL DECISION,ORTHOGRAPHIC NEIGHBORHOOD,FREQUENCY,ACCESS,SIMILARITY,ACTIVATION,LANGUAGE,ACCOUNT,TASK}},\n  language     = {{eng}},\n  number       = {{6}},\n  pages        = {{1502--1508}},\n  publisher    = {{AMER PSYCHOLOGICAL ASSOC/EDUCATIONAL PUBLISHING FOUNDATION}},\n  title        = {{Testing the Multiple in the multiple read-out model of visual word recognition}},\n  url          = {{http://doi.org/10.1037/0278-7393.31.6.1502}},\n  volume       = {{31}},\n  year         = {{2005}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n Two-digit comparison - Decomposed, holistic, or hybrid?.\n \n \n \n\n\n \n Verguts, Tom; and De Moor, W.\n\n\n \n\n\n\n EXPERIMENTAL PSYCHOLOGY, 52(3): 195–200. 2005.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{350346,\n  author       = {{Verguts, Tom and De Moor, Wendy}},\n  issn         = {{1618-3169}},\n  journal      = {{EXPERIMENTAL PSYCHOLOGY}},\n  language     = {{eng}},\n  number       = {{3}},\n  pages        = {{195--200}},\n  publisher    = {{HOGREFE & HUBER PUBLISHERS}},\n  title        = {{Two-digit comparison - Decomposed, holistic, or hybrid?}},\n  volume       = {{52}},\n  year         = {{2005}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n Dissociation of the distance effect and size effect in one-digit numbers.\n \n \n \n\n\n \n Verguts, Tom; and Van Opstal, F.\n\n\n \n\n\n\n PSYCHONOMIC BULLETIN & REVIEW, 12(5): 925–930. 2005.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{350891,\n  author       = {{Verguts, Tom and Van Opstal, Filip}},\n  issn         = {{1069-9384}},\n  journal      = {{PSYCHONOMIC BULLETIN & REVIEW}},\n  language     = {{eng}},\n  number       = {{5}},\n  pages        = {{925--930}},\n  publisher    = {{PSYCHONOMIC SOC INC}},\n  title        = {{Dissociation of the distance effect and size effect in one-digit numbers}},\n  volume       = {{12}},\n  year         = {{2005}},\n}\n\n

\n

\n\n\n\n

\n\n\n\n\n\n

\n

\n \n 2004\n \n \n (5)\n \n \n

\n

\n \n \n

\n \n\n \n \n \n \n \n Assessing the informational value of parameter estimates in cognitive models.\n \n \n \n\n\n \n Verguts, Tom; and STORMS, G\n\n\n \n\n\n\n BEHAVIOR RESEARCH METHODS INSTRUMENTS & COMPUTERS, 36(1): 1–10. 2004.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{293462,\n  author       = {{Verguts, Tom and STORMS, G}},\n  issn         = {{0743-3808}},\n  journal      = {{BEHAVIOR RESEARCH METHODS INSTRUMENTS & COMPUTERS}},\n  language     = {{eng}},\n  number       = {{1}},\n  pages        = {{1--10}},\n  publisher    = {{PSYCHONOMIC SOC INC}},\n  title        = {{Assessing the informational value of parameter estimates in cognitive models}},\n  volume       = {{36}},\n  year         = {{2004}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n Measures of similarity in models of categorization.\n \n \n \n\n\n \n Verguts, Tom; AMEEL, E; and STORMS, G\n\n\n \n\n\n\n MEMORY & COGNITION, 32(3): 379–389. 2004.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{294383,\n  author       = {{Verguts, Tom and AMEEL, E and STORMS, G}},\n  issn         = {{0090-502X}},\n  journal      = {{MEMORY & COGNITION}},\n  language     = {{eng}},\n  number       = {{3}},\n  pages        = {{379--389}},\n  publisher    = {{PSYCHONOMIC SOC INC}},\n  title        = {{Measures of similarity in models of categorization}},\n  volume       = {{32}},\n  year         = {{2004}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n Modèles de la ligne numérique mentale.\n \n \n \n\n\n \n Verguts, Tom; and Fias, W.\n\n\n \n\n\n\n In La Cognition Numérique, pages 95–110. Hermes Science Publications, 2004.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@incollection{294592,\n  author       = {{Verguts, Tom and Fias, Wim}},\n  booktitle    = {{La Cognition Numérique}},\n  isbn         = {{2-7462-0826-1}},\n  language     = {{eng}},\n  pages        = {{95--110}},\n  publisher    = {{Hermes Science Publications}},\n  title        = {{Modèles de la ligne numérique mentale}},\n  year         = {{2004}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n Representation of number in animals and humans: A neural model.\n \n \n \n\n\n \n Verguts, Tom; and Fias, W.\n\n\n \n\n\n\n JOURNAL OF COGNITIVE NEUROSCIENCE, 16(9): 1493–1504. 2004.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{302999,\n  author       = {{Verguts, Tom and Fias, Wim}},\n  issn         = {{0898-929X}},\n  journal      = {{JOURNAL OF COGNITIVE NEUROSCIENCE}},\n  language     = {{eng}},\n  number       = {{9}},\n  pages        = {{1493--1504}},\n  publisher    = {{M I T PRESS}},\n  title        = {{Representation of number in animals and humans: A neural model}},\n  volume       = {{16}},\n  year         = {{2004}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n The mental number line: exact and approximate.\n \n \n \n\n\n \n Fias, Wim; and Verguts, T.\n\n\n \n\n\n\n 2004.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@misc{303000,\n  author       = {{Fias, Wim and Verguts, Tom}},\n  issn         = {{1364-6613}},\n  language     = {{eng}},\n  number       = {{10}},\n  pages        = {{447--448}},\n  publisher    = {{ELSEVIER SCIENCE LONDON}},\n  series       = {{TRENDS IN COGNITIVE SCIENCES}},\n  title        = {{The mental number line: exact and approximate}},\n  volume       = {{8}},\n  year         = {{2004}},\n}\n\n

\n

\n\n\n\n

\n\n\n\n\n\n

\n

\n \n 2003\n \n \n (3)\n \n \n

\n

\n \n \n

\n \n\n \n \n \n \n \n Determinants of speeded categorization in natural concepts.\n \n \n \n\n\n \n VERBEEMEN, T; STORMS, G; and Verguts, T.\n\n\n \n\n\n\n PSYCHOLOGICA BELGICA, 43(3): 139–151. 2003.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{212107,\n  author       = {{VERBEEMEN, T and STORMS, G and Verguts, Tom}},\n  issn         = {{0033-2879}},\n  journal      = {{PSYCHOLOGICA BELGICA}},\n  language     = {{eng}},\n  number       = {{3}},\n  pages        = {{139--151}},\n  publisher    = {{BELGIAN PSYCHOL SOC}},\n  title        = {{Determinants of speeded categorization in natural concepts}},\n  volume       = {{43}},\n  year         = {{2003}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n Implementation intentions do not enhance all types of goals: The moderating role of goal difficulty.\n \n \n \n\n\n \n DEWITTE, S; Verguts, T.; and LENS, W\n\n\n \n\n\n\n CURRENT PSYCHOLOGY, 22(1): 73–89. 2003.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{212110,\n  author       = {{DEWITTE, S and Verguts, Tom and LENS, W}},\n  issn         = {{1046-1310}},\n  journal      = {{CURRENT PSYCHOLOGY}},\n  language     = {{eng}},\n  number       = {{1}},\n  pages        = {{73--89}},\n  publisher    = {{TRANSACTION PERIOD CONSORTIUM}},\n  title        = {{Implementation intentions do not enhance all types of goals: The moderating role of goal difficulty}},\n  volume       = {{22}},\n  year         = {{2003}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n Decision-bound theory and the influence of familiarity.\n \n \n \n\n\n \n Verguts, Tom; STORMS, G; and TUERLINCKX, F\n\n\n \n\n\n\n PSYCHONOMIC BULLETIN & REVIEW, 10(1): 141–148. 2003.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{212113,\n  author       = {{Verguts, Tom and STORMS, G and TUERLINCKX, F}},\n  issn         = {{1069-9384}},\n  journal      = {{PSYCHONOMIC BULLETIN & REVIEW}},\n  language     = {{eng}},\n  number       = {{1}},\n  pages        = {{141--148}},\n  publisher    = {{PSYCHONOMIC SOC INC}},\n  title        = {{Decision-bound theory and the influence of familiarity}},\n  volume       = {{10}},\n  year         = {{2003}},\n}\n\n

\n

\n\n\n\n

\n\n\n\n\n\n

\n

\n \n 2002\n \n \n (2)\n \n \n

\n

\n \n \n

\n \n\n \n \n \n \n \n The induction of solution rules in Raven's Progressive Matrices Test.\n \n \n \n\n\n \n Verguts, Tom; and DE BOECK, P\n\n\n \n\n\n\n EUROPEAN JOURNAL OF COGNITIVE PSYCHOLOGY, 14(4): 521–547. 2002.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{159007,\n  author       = {{Verguts, Tom and DE BOECK, P}},\n  issn         = {{0954-1446}},\n  journal      = {{EUROPEAN JOURNAL OF COGNITIVE PSYCHOLOGY}},\n  language     = {{eng}},\n  number       = {{4}},\n  pages        = {{521--547}},\n  title        = {{The induction of solution rules in Raven's Progressive Matrices Test.}},\n  volume       = {{14}},\n  year         = {{2002}},\n}\n\n

\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n A dynamic model for rule induction tasks.\n \n \n \n\n\n \n Verguts, Tom; MARIS, E; and DE BOECK, P\n\n\n \n\n\n\n JOURNAL OF MATHEMATICAL PSYCHOLOGY, 46(4): 455–485. 2002.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{159018,\n  author       = {{Verguts, Tom and MARIS, E and DE BOECK, P}},\n  issn         = {{0022-2496}},\n  journal      = {{JOURNAL OF MATHEMATICAL PSYCHOLOGY}},\n  language     = {{eng}},\n  number       = {{4}},\n  pages        = {{455--485}},\n  title        = {{A dynamic model for rule induction tasks.}},\n  volume       = {{46}},\n  year         = {{2002}},\n}\n\n

\n

\n\n\n\n

\n\n\n\n\n\n

\n

\n \n 2001\n \n \n (3)\n \n \n

\n

\n \n \n

\n \n\n \n \n \n \n \n \n Being funny : a selectionist account of humor production.\n \n \n \n \n\n\n \n Dewitte, Siegfried; and Verguts, T.\n\n\n \n\n\n\n HUMOR-INTERNATIONAL JOURNAL OF HUMOR RESEARCH, 14(1): 37–53. 2001.\n \n\n\n\n
\n\n\n\n \n \n $\"Being$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

\n

@article{8501083,\n  abstract     = {{In this paper, we develop a theory to explain why some people possess a good sense of humour (i.e., are funny) while others do not. In essence, the theory follows the general selectionist (Donahoe and Palmer 1994) scheme of response generation and selection. People who both generate a lot of jokes and are sensitive to negative appraisal will be considered to be humerous by their peers. Data to test this theory are described and analyzed. Most results are in accord with our theory and alternative explanations are ruled out.}},\n  author       = {{Dewitte, Siegfried and Verguts, Tom}},\n  issn         = {{0933-1719}},\n  journal      = {{HUMOR-INTERNATIONAL JOURNAL OF HUMOR RESEARCH}},\n  keywords     = {{CARTOONS,SENSE}},\n  language     = {{eng}},\n  number       = {{1}},\n  pages        = {{37--53}},\n  publisher    = {{Walter De Gruyter & Co}},\n  title        = {{Being funny : a selectionist account of humor production}},\n  url          = {{http://doi.org/10.1515/humr.14.1.37}},\n  volume       = {{14}},\n  year         = {{2001}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Some Mantel-Haenszel tests of Rasch model assumptions.\n \n \n \n \n\n\n \n Verguts, Tom; and De Boeck, P.\n\n\n \n\n\n\n BRITISH JOURNAL OF MATHEMATICAL & STATISTICAL PSYCHOLOGY, 54: 21–37. 2001.\n \n\n\n\n
\n\n\n\n \n \n $\"Some$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8501084,\n  abstract     = {{A class of Rasch model tests is proposed, all of them based on the Manter-Haenszel chi-squared statistic. All tests make use of the 'sufficient statistics' property the Rasch model possesses. One element of our general class, the test for item bias developed by Holland and Thayer, has been discussed extensively in the psychometric literature. Three applications of the general procedure are presented, two on unidimensionality and one on item dependence in educational testing. In each case, simulation results are reported. Our procedure is also applied to real data.}},\n  author       = {{Verguts, Tom and De Boeck, Paul}},\n  issn         = {{0007-1102}},\n  journal      = {{BRITISH JOURNAL OF MATHEMATICAL & STATISTICAL PSYCHOLOGY}},\n  keywords     = {{PERFORMANCE,STATISTICS,FIT}},\n  language     = {{eng}},\n  pages        = {{21--37}},\n  publisher    = {{British Psychological Soc}},\n  title        = {{Some Mantel-Haenszel tests of Rasch model assumptions}},\n  url          = {{http://doi.org/10.1348/000711001159401}},\n  volume       = {{54}},\n  year         = {{2001}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n On the correlation between working memory capacity and performance on intelligence tests.\n \n \n \n \n\n\n \n Verguts, Tom; and De Boeck, P.\n\n\n \n\n\n\n LEARNING AND INDIVIDUAL DIFFERENCES, 13(1): PII S1041-6080(02)00049-3:37–PII S1041-6080(02)00049-3:55. 2001.\n \n\n\n\n
\n\n\n\n \n \n $\"On$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8501086,\n  abstract     = {{A ubiquitous finding in intelligence research is that there is a substantial correlation between working memory (WM) capacity and general (fluid) intelligence tests (e.g., [Intelligence 14 (1990) 389]). The standard explanation for this correlation is as follows: People with high WM capacity can keep in memory many elements and are therefore good at storing subresults needed within an item. We argue that another factor may be partly responsible for this correlation, namely, that people with a high WM capacity can store many solution principles over items. Two experiments (with N=42 and N=52, respectively) are conducted that validate this alternative explanation in two particular tests, the Raven Advanced Progressive Matrices Test (RPM) [Raven, J. C. (1965). Advanced progressive matrices, set H. New York: Psychological Corporation], and a number series test constructed by ourselves, but resembling standard number series intelligence tests (e.g., [J Educ Psychol 75 (1983) 603]). (C) 2002 Elsevier Science Inc. All rights reserved.}},\n  articleno    = {{PII S1041-6080(02)00049-3}},\n  author       = {{Verguts, Tom and De Boeck, Paul}},\n  issn         = {{1041-6080}},\n  journal      = {{LEARNING AND INDIVIDUAL DIFFERENCES}},\n  keywords     = {{PROGRESSIVE MATRICES TEST,ADULT AGE-DIFFERENCES,INDIVIDUAL-DIFFERENCES,FLUID INTELLIGENCE,COMPREHENSION,COMPLEXITY,ABILITY,SPEED}},\n  language     = {{eng}},\n  number       = {{1}},\n  pages        = {{PII S1041-6080(02)00049-3:37--PII S1041-6080(02)00049-3:55}},\n  publisher    = {{Elsevier Science Bv}},\n  title        = {{On the correlation between working memory capacity and performance on intelligence tests}},\n  url          = {{http://doi.org/10.1016/S1041-6080(02)00049-3}},\n  volume       = {{13}},\n  year         = {{2001}},\n}\n\n

\n

\n\n\n\n\n\n

\n

\n \n 2000\n \n \n (2)\n \n \n

\n

\n \n \n

\n \n\n \n \n \n \n \n \n A Rasch model for detecting learning while solving an intelligence test.\n \n \n \n \n\n\n \n Verguts, Tom; and De Boeck, P.\n\n\n \n\n\n\n APPLIED PSYCHOLOGICAL MEASUREMENT, 24(2): 151–162. 2000.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{8501092,\n  abstract     = {{A dynamic extension of the Rasch model (Verhelst & Glas, 1993, 1995) is developed from a Bayesian point of view, and it is shown how this permits application of the model in a wide variety of test settings. In particular, the method allows for an adequate modeling of learning throughout a test, determining whether learning has occurred and whether individual differences in learning rate should be assumed. An example is provided in which the model is applied to a computer-administered intelligence test. A satisfactory fit of the model was found for these data. Results indicated that learning did occur, and that there might be individual differences in learning rate. Index terms: Bayesian statistics, dynamic Rasch model, intelligence tests, learning, Rasch model.}},\n  author       = {{Verguts, Tom and De Boeck, Paul}},\n  issn         = {{0146-6216}},\n  journal      = {{APPLIED PSYCHOLOGICAL MEASUREMENT}},\n  language     = {{eng}},\n  number       = {{2}},\n  pages        = {{151--162}},\n  title        = {{A Rasch model for detecting learning while solving an intelligence test}},\n  url          = {{http://doi.org/10.1177/01466210022031589}},\n  volume       = {{24}},\n  year         = {{2000}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n A note on the Martin-Löf test for unidimensionality.\n \n \n \n\n\n \n Verguts, Tom; and De Boeck, P.\n\n\n \n\n\n\n METHODS OF PSYCHOLOGICAL RESEARCH, 5(1). 2000.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{8511121,\n  author       = {{Verguts, Tom and De Boeck, Paul}},\n  issn         = {{1432-8534}},\n  journal      = {{METHODS OF PSYCHOLOGICAL RESEARCH}},\n  language     = {{eng}},\n  number       = {{1}},\n  title        = {{A note on the Martin-Löf test for unidimensionality}},\n  volume       = {{5}},\n  year         = {{2000}},\n}\n\n

\n

\n\n\n\n

\n\n\n\n\n\n

\n

\n \n 1999\n \n \n (2)\n \n \n

\n

\n \n \n

\n \n\n \n \n \n \n \n Behavioral variation : a neglected aspect in selectionist thinking.\n \n \n \n\n\n \n Dewitte, Siegfried; and Verguts, T.\n\n\n \n\n\n\n BEHAVIOR AND PHILOSOPHY, 27(2): 127–145. 1999.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8501093,\n  abstract     = {{A selectionist approach to human ontogenetic development relies on three basic processes: variation, selection, and retention. The approach further implies chat for adaptive behavior to emerge during development, each of these processes is required. Nevertheless, to date variation has been relatively neglected. Some studies show that behavioral variability is enhanced when the appropriate contingencies are present. Moreover, behavioral variability has been shown to facilitate the acquisition of difficult behaviors in animals (e.g., Neuringer, 1993). In the first part of the present paper, we briefly recapitulate the basic tenets of selectionist psychology and attempt to explore the role of behavioral variability in human behavior. In the second pare, its importance in the emergence of intelligence, humor production, and self-regulation is discussed. We present data suggesting that variability enhances intelligent behavior, qualitative humor production and effective self-regulation.}},\n  author       = {{Dewitte, Siegfried and Verguts, Tom}},\n  issn         = {{1053-8348}},\n  journal      = {{BEHAVIOR AND PHILOSOPHY}},\n  keywords     = {{VARIABILITY,OPERANT,HUMOR,COGNITION,SEQUENCES,FREQUENCY,WORKING,SELF}},\n  language     = {{eng}},\n  number       = {{2}},\n  pages        = {{127--145}},\n  publisher    = {{Cambridge Center Behavioral Studies}},\n  title        = {{Behavioral variation : a neglected aspect in selectionist thinking}},\n  volume       = {{27}},\n  year         = {{1999}},\n}\n\n

\n

\n\n\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Generation speed in Raven's progressive matrices test.\n \n \n \n \n\n\n \n Verguts, Tom; De Boeck, P.; and Maris, E.\n\n\n \n\n\n\n INTELLIGENCE, 27(4): 329–345. 1999.\n \n\n\n\n
\n\n\n\n \n \n $\"Generation$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

\n

@article{8501097,\n  abstract     = {{In this paper, we investigate the role of response fluency on a well-known intelligence test, Raven's Advanced Progressive Matrices (APM) test. Finding rules that govern the items is critical in solving this test. Finding these rules is conceptualized as sampling rules from a (statistical) rule distribution until the correct one is attained. Response fluency is then seen as generation speed, or the speed at which a person generates (samples) rules from this distribution. We develop a test that isolates this speed of sampling variable, and a method to check whether this variable was adequately isolated. The score on this test is then compared with performance on the APM test. It is found that the speed at which people sample from such distributions is an important variable in solving APM items.}},\n  author       = {{Verguts, Tom and De Boeck, Paul and Maris, Eric}},\n  issn         = {{0160-2896}},\n  journal      = {{INTELLIGENCE}},\n  keywords     = {{WORKING-MEMORY CAPACITY,CONDUCTION-VELOCITY,SYNONYM TASKS,INTELLIGENCE,COMPLEXITY,MODELS}},\n  language     = {{eng}},\n  number       = {{4}},\n  pages        = {{329--345}},\n  publisher    = {{Elsevier Science Inc}},\n  title        = {{Generation speed in Raven's progressive matrices test}},\n  url          = {{http://doi.org/10.1016/S0160-2896(99)00023-9}},\n  volume       = {{27}},\n  year         = {{1999}},\n}\n\n

\n

\n\n\n\n\n\n

\n

\n \n 1998\n \n \n (1)\n \n \n

\n

\n \n \n

\n \n\n \n \n \n \n \n \n Analyzing experimental data using the Rasch model.\n \n \n \n \n\n\n \n Verguts, Tom; De Boeck, P.; and Storms, G.\n\n\n \n\n\n\n BEHAVIOR RESEARCH METHODS INSTRUMENTS & COMPUTERS, 30(3): 501–505. 1998.\n \n\n\n\n
\n\n\n\n \n \n $\"Analyzing$ Paper\n \n \n\n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n\n\n\n

\n

@article{8501091,\n  abstract     = {{We present a method for studying experimental data based on a psychometric model, the "Rasch model" (Rasch, 1966; Thissen & Steinberg, 1986). We illustrate the method with the use of a data set in the field of concept research. More specifically, we investigate whether a conjunctive concept can be seen as an additive combination of its constituents. High correlations between model and data are obtained, but a formal goodness-of-fit test indicates that the model does not completely account for the data. We then alter the Rasch model in such a way as to capture our idea of why the model deviates from the data. This results in higher correlations and a strong increase in goodness-of-fit. It is concluded that our ideas, as incorporated in the model, adequately summarize the data. More generally, this research illustrates that applying the Rasch model and altering it according to one's hypotheses is an excellent way to analyze experimental data.}},\n  author       = {{Verguts, Tom and De Boeck, Paul and Storms, Gert}},\n  issn         = {{0743-3808}},\n  journal      = {{BEHAVIOR RESEARCH METHODS INSTRUMENTS & COMPUTERS}},\n  keywords     = {{CONCEPT CONJUNCTIONS,RESPONSE MODELS}},\n  language     = {{eng}},\n  number       = {{3}},\n  pages        = {{501--505}},\n  publisher    = {{Psychonomic Soc Inc}},\n  title        = {{Analyzing experimental data using the Rasch model}},\n  url          = {{http://doi.org/10.3758/BF03200683}},\n  volume       = {{30}},\n  year         = {{1998}},\n}\n\n

\n

\n\n\n\n\n\n

\n