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\n \n 2018\n \n \n (1)\n \n \n

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\n \n\n \n \n \n \n \n \n Identification of autism spectrum disorder using deep learning and the ABIDE dataset.\n \n \n \n \n\n\n \n Heinsfeld, A. S.; Franco, A. R.; Craddock, R. C.; Buchweitz, A.; and Meneguzzi, F.\n\n\n \n\n\n\n NeuroImage: Clinical, 17: 16 - 23. 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Identification$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\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\n\n\n

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@article{HEINSFELD201816,\ntitle = "Identification of autism spectrum disorder using deep learning and the ABIDE dataset",\njournal = "NeuroImage: Clinical",\nvolume = "17",\npages = "16 - 23",\nyear = "2018",\nissn = "2213-1582",\ndoi = "https://doi.org/10.1016/j.nicl.2017.08.017",\nurl = "http://www.sciencedirect.com/science/article/pii/S2213158217302073",\nauthor = "Anibal Sólon Heinsfeld and Alexandre Rosa Franco and R. Cameron Craddock and Augusto Buchweitz and Felipe Meneguzzi",\nkeywords = "Autism, fMRI, ABIDE, Resting state, Deep learning"\n}\n

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\n \n 2017\n \n \n (1)\n \n \n

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\n \n\n \n \n \n \n \n \n Decreased comfort food intake and allostatic load in adolescents carrying the A3669G variant of the glucocorticoid receptor gene.\n \n \n \n \n\n\n \n Rodrigues, D. M.; Reis, R. S.; Dalle Molle, R.; Machado, T. D.; Mucellini, A. B.; Bortoluzzi, A.; Toazza, R.; Pérez, J. A.; Salum, G. A.; Agranonik, M.; Minuzzi, L.; Levitan, R. D; Buchweitz, A.; Franco, A. R.; Manfro, G. G.; and Silveira, P. P.\n\n\n \n\n\n\n Appetite, 116: 21–28. sep 2017.\n \n\n\n\n
\n\n\n\n \n \n $\"Decreased$ Paper\n \n \n\n \n \n doi\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

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@article{Rodrigues2017,\nauthor = {Rodrigues, Danitsa Marcos and Reis, Roberta Sena and {Dalle Molle}, Roberta and Machado, Tania Diniz and Mucellini, Amanda Brondani and Bortoluzzi, Andressa and Toazza, Rudineia and P{\\'{e}}rez, Juliano Adams and Salum, Giovanni Abrah{\\~{a}}o and Agranonik, Marilyn and Minuzzi, Luciano and Levitan, Robert D and Buchweitz, Augusto and Franco, Alexandre Rosa and Manfro, Gisele Gus and Silveira, Patr{\\'{i}}cia Pelufo},\ndoi = {10.1016/j.appet.2017.04.004},\nfile = {::},\nissn = {01956663},\njournal = {Appetite},\nkeywords = {glucocorticoid receptor gene polymorphism},\nmonth = {sep},\npages = {21--28},\ntitle = {{Decreased comfort food intake and allostatic load in adolescents carrying the A3669G variant of the glucocorticoid receptor gene}},\nurl = {http://linkinghub.elsevier.com/retrieve/pii/S0195666316308133},\nvolume = {116},\nyear = {2017}\n}\n

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\n \n 2016\n \n \n (6)\n \n \n

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\n \n\n \n \n \n \n \n \n Increased brain cortical thickness associated with visceral fat in adolescents.\n \n \n \n \n\n\n \n Saute, R L; Soder, R B; Alves Filho, J O; Baldisserotto, M; and Franco, A R\n\n\n \n\n\n\n Pediatric obesity,3–6. 2016.\n \n\n\n\n
\n\n\n\n \n \n $\"Increased$ Paper\n \n \n\n \n \n doi\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

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@article{Saute2016,\nabstract = {BACKGROUND There has been a growing amount of evidence indicating that excess visceral fat is associated with alterations in brain structure and function, including brain cortical thinning in adults. OBJECTIVES This study aims to investigate the relationship between brain cortical thickness with obesity assessments, in adolescents. METHODS In this study, we measured three different obesity assessments within an adolescent population (aged 15 - 18 years): body mass index (BMI), visceral fat ratio measured with an MRI and hepatorenal gradient measured with an ultrasound. Volunteers also underwent an MRI scan to measure brain structure. RESULTS Results indicated that there was no relationship of BMI or hepatorenal gradient with brain cortical dimensions. However, there was a significant association between visceral fat ratio and an increase of cortical thickness throughout the brain. CONCLUSIONS These results suggest that visceral fat, but not BMI, is correlated with cortical thickening in adolescence.},\nauthor = {Saute, R L and Soder, R B and {Alves Filho}, J O and Baldisserotto, M and Franco, A R},\ndoi = {10.1111/ijpo.12190},\nfile = {:Users/10084029/Documents/PAPERS/Saute{\\_}et{\\_}al-2016-Pediatric{\\_}Obesity.pdf:pdf},\nissn = {2047-6310},\njournal = {Pediatric obesity},\nkeywords = {MRI,adolescent obesity,cortical thickness,intra-abdominal fat},\npages = {3--6},\npmid = {27788560},\ntitle = {{Increased brain cortical thickness associated with visceral fat in adolescents.}},\nurl = {http://www.ncbi.nlm.nih.gov/pubmed/27788560},\nyear = {2016}\n}\n

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\n \n\n \n \n \n \n \n \n Amygdala-based intrinsic functional connectivity and anxiety disorders in adolescents and young adults.\n \n \n \n \n\n\n \n Toazza, R.; Franco, A. R.; Buchweitz, A.; Molle, R. D.; Rodrigues, D. M.; Reis, R. S.; Mucellini, A. B.; Esper, N. B.; Aguzzoli, C.; Silveira, P. P.; Salum, G. A.; and Manfro, G. G.\n\n\n \n\n\n\n Psychiatry Research: Neuroimaging, 257(April): 11–16. nov 2016.\n \n\n\n\n
\n\n\n\n \n \n $\"Amygdala-based$ Paper\n \n \n\n \n \n doi\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{Toazza2016,\nauthor = {Toazza, Rudineia and Franco, Alexandre Rosa and Buchweitz, Augusto and Molle, Roberta Dalle and Rodrigues, Danitsa Marcos and Reis, Roberta Sena and Mucellini, Amanda Brondani and Esper, Nathalia Bianchini and Aguzzoli, Cristiano and Silveira, Patr{\\'{i}}cia Pelufo and Salum, Giovanni Abrah{\\~{a}}o and Manfro, Gisele Gus},\ndoi = {10.1016/j.pscychresns.2016.09.010},\nfile = {:Users/10084029/Library/Application Support/Mendeley Desktop/Downloaded/Toazza et al. - 2016 - Amygdala-based intrinsic functional connectivity and anxiety disorders in adolescents and young adults.pdf:pdf},\nissn = {09254927},\njournal = {Psychiatry Research: Neuroimaging},\nkeywords = {Cognitive neuroscience,FMRI,Probabilistic maps,Psychiatry disorders},\nmonth = {nov},\nnumber = {April},\npages = {11--16},\npublisher = {Elsevier},\ntitle = {{Amygdala-based intrinsic functional connectivity and anxiety disorders in adolescents and young adults}},\nurl = {http://linkinghub.elsevier.com/retrieve/pii/S0925492716300944},\nvolume = {257},\nyear = {2016}\n}\n

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\n \n\n \n \n \n \n \n \n Interaction between perceived maternal care, anxiety symptoms, and the neurobehavioral response to palatable foods in adolescents.\n \n \n \n \n\n\n \n Machado, T. D.; Dalle Molle, R.; Reis, R. S.; Rodrigues, D. M.; Mucellini, A. B.; Minuzzi, L.; Franco, A. R.; Buchweitz, A.; Toazza, R.; Ergang, B. C.; Cunha, A. C. d. A.; Salum, G. A.; Manfro, G. G.; and Silveira, P. P.\n\n\n \n\n\n\n Stress, 19(3): 287–294. may 2016.\n \n\n\n\n
\n\n\n\n \n \n $\"Interaction$ Paper\n \n \n\n \n \n doi\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

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@article{Machado2016,\nauthor = {Machado, Tania Diniz and {Dalle Molle}, Roberta and Reis, Roberta Sena and Rodrigues, Danitsa Marcos and Mucellini, Amanda Brondani and Minuzzi, Luciano and Franco, Alexandre Rosa and Buchweitz, Augusto and Toazza, Rudineia and Ergang, B{\\'{a}}rbara Cristina and Cunha, Ana Carla de Ara{\\'{u}}jo and Salum, Giovanni Abrah{\\~{a}}o and Manfro, Gisele Gus and Silveira, Patr{\\'{i}}cia Pelufo},\ndoi = {10.1080/10253890.2016.1191464},\nfile = {:Users/10084029/Library/Application Support/Mendeley Desktop/Downloaded/Machado et al. - 2016 - Interaction between perceived maternal care, anxiety symptoms, and the neurobehavioral response to palatable foo.pdf:pdf},\nissn = {1025-3890},\njournal = {Stress},\nmonth = {may},\nnumber = {3},\npages = {287--294},\ntitle = {{Interaction between perceived maternal care, anxiety symptoms, and the neurobehavioral response to palatable foods in adolescents}},\nurl = {http://www.tandfonline.com/doi/full/10.1080/10253890.2016.1191464},\nvolume = {19},\nyear = {2016}\n}\n

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\n \n\n \n \n \n \n \n \n Brainhack: a collaborative workshop for the open neuroscience community.\n \n \n \n \n\n\n \n Cameron Craddock, R.; S. Margulies, D.; Bellec, P.; Nolan Nichols, B.; Alcauter, S.; A. Barrios, F.; Burnod, Y.; J. Cannistraci, C.; Cohen-Adad, J.; De Leener, B.; Dery, S.; Downar, J.; Dunlop, K.; R. Franco, A.; Seligman Froehlich, C.; J. Gerber, A.; S. Ghosh, S.; J. Grabowski, T.; Hill, S.; Sólon Heinsfeld, A.; Matthew Hutchison, R.; Kundu, P.; R. Laird, A.; Liew, S.; J. Lurie, D.; G. McLaren, D.; Meneguzzi, F.; Mennes, M.; Mesmoudi, S.; O'Connor, D.; H. Pasaye, E.; Peltier, S.; Poline, J.; Prasad, G.; Fraga Pereira, R.; Quirion, P.; Rokem, A.; S. Saad, Z.; Shi, Y.; C. Strother, S.; Toro, R.; Q. Uddin, L.; D. Van Horn, J.; W. Van Meter, J.; C. Welsh, R.; and Xu, T.\n\n\n \n\n\n\n GigaScience, 5(1): 16. 2016.\n \n\n\n\n
\n\n\n\n \n \n $\"Brainhack:$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\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 \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

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@article{CameronCraddock2016,\nauthor = {{Cameron Craddock}, R. and {S. Margulies}, Daniel and Bellec, Pierre and {Nolan Nichols}, B. and Alcauter, Sarael and {A. Barrios}, Fernando and Burnod, Yves and {J. Cannistraci}, Christopher and Cohen-Adad, Julien and {De Leener}, Benjamin and Dery, Sebastien and Downar, Jonathan and Dunlop, Katharine and {R. Franco}, Alexandre and {Seligman Froehlich}, Caroline and {J. Gerber}, Andrew and {S. Ghosh}, Satrajit and {J. Grabowski}, Thomas and Hill, Sean and {S{\\'{o}}lon Heinsfeld}, Anibal and {Matthew Hutchison}, R. and Kundu, Prantik and {R. Laird}, Angela and Liew, Sook-Lei and {J. Lurie}, Daniel and {G. McLaren}, Donald and Meneguzzi, Felipe and Mennes, Maarten and Mesmoudi, Salma and O'Connor, David and {H. Pasaye}, Erick and Peltier, Scott and Poline, Jean-Baptiste and Prasad, Gautam and {Fraga Pereira}, Ramon and Quirion, Pierre-Olivier and Rokem, Ariel and {S. Saad}, Ziad and Shi, Yonggang and {C. Strother}, Stephen and Toro, Roberto and {Q. Uddin}, Lucina and {D. Van Horn}, John and {W. Van Meter}, John and {C. Welsh}, Robert and Xu, Ting},\ndoi = {10.1186/s13742-016-0121-x},\nfile = {:Users/10084029/Library/Application Support/Mendeley Desktop/Downloaded/Cameron Craddock et al. - 2016 - Brainhack a collaborative workshop for the open neuroscience community.pdf:pdf},\nissn = {2047-217X},\njournal = {GigaScience},\nkeywords = {Hackathon,Unconference,Open science,Neuroscience,D,and data,collaboration,data sharing,hackathon,introducing brainhack,networking,neuroscience,open science,open science promotes collaboration,parent dissemination of ideas,through the trans-,tools,unconference,with the},\nnumber = {1},\npages = {16},\npublisher = {GigaScience},\ntitle = {{Brainhack: a collaborative workshop for the open neuroscience community}},\nurl = {http://gigascience.biomedcentral.com/articles/10.1186/s13742-016-0121-x},\nvolume = {5},\nyear = {2016}\n}\n

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\n \n\n \n \n \n \n \n \n Intrinsic Brain Connectivity Following Long-Term Treatment with Methylphenidate in Children with Attention-Deficit/Hyperactivity Disorder.\n \n \n \n \n\n\n \n Battel, L.; Kieling, R. R.; Kieling, C.; Anés, M.; Aurich, N. K.; da Costa, J. C.; Rohde, L. A.; and Franco, A. R.\n\n\n \n\n\n\n Journal of Child and Adolescent Psychopharmacology, 26(6): 555–561. aug 2016.\n \n\n\n\n
\n\n\n\n \n \n $\"Intrinsic$ Paper\n \n \n\n \n \n doi\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

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@article{Battel2016,\nauthor = {Battel, Lucas and Kieling, Renata R. and Kieling, Christian and An{\\'{e}}s, Maur{\\'{i}}cio and Aurich, Nathassia Kadletz and da Costa, Jaderson Costa and Rohde, Luis Augusto and Franco, Alexandre Rosa},\ndoi = {10.1089/cap.2015.0221},\nfile = {:Users/10084029/Library/Application Support/Mendeley Desktop/Downloaded/Battel et al. - 2016 - Intrinsic Brain Connectivity Following Long-Term Treatment with Methylphenidate in Children with Attention-Defici.pdf:pdf},\nissn = {1044-5463},\njournal = {Journal of Child and Adolescent Psychopharmacology},\nmonth = {aug},\nnumber = {6},\npages = {555--561},\ntitle = {{Intrinsic Brain Connectivity Following Long-Term Treatment with Methylphenidate in Children with Attention-Deficit/Hyperactivity Disorder}},\nurl = {http://online.liebertpub.com/doi/10.1089/cap.2015.0221},\nvolume = {26},\nyear = {2016}\n}\n

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\n \n\n \n \n \n \n \n \n Impulsivity-based thrifty eating phenotype and the protective role of n-3 PUFAs intake in adolescents.\n \n \n \n \n\n\n \n Reis, R S; Molle, R D.; Machado, T D; Mucellini, A B; Rodrigues, D M; Bortoluzzi, A; Bigonha, S M; Toazza, R; Salum, G A; and Minuzzi, L\n\n\n \n\n\n\n Translational Psychiatry, 6(October 2015): e755. mar 2016.\n \n\n\n\n
\n\n\n\n \n \n $\"Impulsivity-based$ Paper\n \n \n\n \n \n doi\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

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@article{Reis2016,\nauthor = {Reis, R S and Molle, R Dalle and Machado, T D and Mucellini, A B and Rodrigues, D M and Bortoluzzi, A and Bigonha, S M and Toazza, R and Salum, G A and Minuzzi, L},\ndoi = {10.1038/tp.2016.16},\nfile = {:Users/10084029/Library/Application Support/Mendeley Desktop/Downloaded/Reis et al. - 2016 - Impulsivity-based thrifty eating phenotype and the protective role of n-3 PUFAs intake in adolescents.pdf:pdf},\nissn = {2158-3188},\njournal = {Translational Psychiatry},\nmonth = {mar},\nnumber = {October 2015},\npages = {e755},\ntitle = {{Impulsivity-based thrifty eating phenotype and the protective role of n-3 PUFAs intake in adolescents}},\nurl = {http://www.nature.com/doifinder/10.1038/tp.2016.16},\nvolume = {6},\nyear = {2016}\n}\n

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\n \n 2015\n \n \n (2)\n \n \n

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\n \n\n \n \n \n \n \n \n Decreasing ADHD phenotypic heterogeneity: searching for neurobiological underpinnings of the restrictive inattentive phenotype.\n \n \n \n \n\n\n \n Ercan, E. S.; Suren, S.; Bacanlı, A.; Yazici, K. U.; Callı, C.; Ozyurt, O.; Aygunes, D.; Kosova, B.; Franco, A. R.; and Rohde, L. A.\n\n\n \n\n\n\n European Child & Adolescent Psychiatry. 2015.\n \n\n\n\n
\n\n\n\n \n \n $\"Decreasing$ Paper\n \n \n\n \n \n doi\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

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@article{Ercan2015,\nauthor = {Ercan, Eyup Sabri and Suren, Serkan and Bacanlı, Ali and Yazici, Kemal Utku and Callı, Cem and Ozyurt, Onur and Aygunes, Duygu and Kosova, Buket and Franco, Alexandre Rosa and Rohde, Luis Augusto},\ndoi = {10.1007/s00787-015-0731-3},\nfile = {:Users/10084029/Library/Application Support/Mendeley Desktop/Downloaded/Ercan et al. - 2015 - Decreasing ADHD phenotypic heterogeneity searching for neurobiological underpinnings of the restrictive inattentiv.pdf:pdf},\nissn = {1018-8827},\njournal = {European Child {\\&} Adolescent Psychiatry},\nkeywords = {1007,ADHD,Hyperactivity,Molecular genetics,Neuroimaging,Neuropsychology,Phenotype,child adolesc psychiatry,decreasing adhd phenotypic heterogeneity,doi 10,original contribution,s00787-015-0731-3,searching},\npublisher = {Springer Berlin Heidelberg},\ntitle = {{Decreasing ADHD phenotypic heterogeneity: searching for neurobiological underpinnings of the restrictive inattentive phenotype}},\nurl = {http://link.springer.com/10.1007/s00787-015-0731-3},\nyear = {2015}\n}\n

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\n \n\n \n \n \n \n \n \n Evaluating the reliability of different preprocessing steps to estimate graph theoretical measures in resting state fMRI data.\n \n \n \n \n\n\n \n Aurich, N. K.; Alves Filho, J. O.; Marques da Silva, A. M.; and Franco, A. R.\n\n\n \n\n\n\n Frontiers in Neuroscience, 9(February): 1–10. feb 2015.\n \n\n\n\n
\n\n\n\n \n \n $\"Evaluating$ Paper\n \n \n\n \n \n doi\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

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@article{Aurich2015,\nauthor = {Aurich, Nathassia K. and {Alves Filho}, Jos{\\~{A}}{\\textcopyright} O. and {Marques da Silva}, Ana M. and Franco, Alexandre R.},\ndoi = {10.3389/fnins.2015.00048},\nissn = {1662-453X},\njournal = {Frontiers in Neuroscience},\nkeywords = {functional MRI,functional mri,graph theory,pre-processing,relia,reliability,resting state},\nmonth = {feb},\nnumber = {February},\npages = {1--10},\ntitle = {{Evaluating the reliability of different preprocessing steps to estimate graph theoretical measures in resting state fMRI data}},\nurl = {http://www.frontiersin.org/Brain{\\_}Imaging{\\_}Methods/10.3389/fnins.2015.00048/abstract http://journal.frontiersin.org/Article/10.3389/fnins.2015.00048/abstract},\nvolume = {9},\nyear = {2015}\n}\n

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\n \n 2014\n \n \n (6)\n \n \n

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\n \n\n \n \n \n \n \n \n CÁLCULO DO VOLUME DO ENCÉFALO ATRAVÉS DE UM CORTE CORONAL MEDIAL.\n \n \n \n \n\n\n \n Filho, J O A.; Peixoto, G G S.; Franco, A R; and Azevedo, D F G\n\n\n \n\n\n\n In XXIV Congresso Brasileiro de Engenharia Biomédica, pages 2405–2408, Uberlândia, MG, Brazil, 2014. \n \n\n\n\n
\n\n\n\n \n \n $\"CÁLCULO$ 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

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@inproceedings{Filho2014,\nabstract = {Baseando-se em uma pr{\\'{a}}tica cl{\\'{i}}nica comum que visa identificar altera{\\c{c}}{\\~{o}}es volum{\\'{e}}tricas no hipocampo, necessita-se normalizar o tamanho do hipocampo pelo volume do enc{\\'{e}}falo para poder comparar os resultados entre os pacientes. Por{\\'{e}}m, para tornar o exame de resson{\\^{a}}ncia magn{\\'{e}}tica mais r{\\'{a}}pido, muitas cl{\\'{i}}nicas somente adquirem cortes coronais em que se inclui o hipocampo, impossibilitando o c{\\'{a}}lculo volum{\\'{e}}trico do enc{\\'{e}}falo. Neste trabalho, foi calculado a rela{\\c{c}}{\\~{a}}o entre o volume do enc{\\'{e}}falo e o volume de um corte coronal com dados de um banco de imagens (N=100). Os resultados mostraram valor m{\\'{e}}dio de 114,64 para a razao volume de enc{\\'{e}}falo/volume do corte com um desvio padr{\\~{a}}o de 4,74. Tais resultados indicaram um fator de normalizacao estatisticamente constante e que pode ser usado como um par{\\^{a}}metro para calcular o volume total do enc{\\'{e}}falo atrav{\\'{e}}s do volume de um corte coronal.},\naddress = {Uberl{\\^{a}}ndia, MG, Brazil},\nauthor = {Filho, J O Alves and Peixoto, G G Schu and Franco, A R and Azevedo, D F G},\nbooktitle = {XXIV Congresso Brasileiro de Engenharia Biom{\\'{e}}dica},\nfile = {:Users/10084029/Library/Application Support/Mendeley Desktop/Downloaded/Filho et al. - 2014 - C{\\'{A}}LCULO DO VOLUME DO ENC{\\'{E}}FALO ATRAV{\\'{E}}S DE UM CORTE CORONAL MEDIAL.pdf:pdf},\nkeywords = {Hipocampo,imagem por resson{\\^{a}}ncia magn{\\'{e}}tica,normaliza{\\c{c}}{\\~{a}}o volum{\\'{e}}trica},\npages = {2405--2408},\ntitle = {{C{\\'{A}}LCULO DO VOLUME DO ENC{\\'{E}}FALO ATRAV{\\'{E}}S DE UM CORTE CORONAL MEDIAL}},\nurl = {http://cbeb.org.br/CBEB2014/index.php/pt/},\nyear = {2014}\n}\n

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\n \n\n \n \n \n \n \n \n Reconciling variable findings of white matter integrity in major depressive disorder.\n \n \n \n \n\n\n \n Choi, K. S.; Holtzheimer, P. E; Franco, A. R; Kelley, M. E; Dunlop, B. W; Hu, X. P; and Mayberg, H. S\n\n\n \n\n\n\n Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology, 39(6): 1332–9. may 2014.\n \n\n\n\n
\n\n\n\n \n \n $\"Reconciling$ Paper\n \n \n\n \n \n doi\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

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@article{Choi2014,\nabstract = {Diffusion tensor imaging (DTI) has been used to evaluate white matter (WM) integrity in major depressive disorder (MDD), with several studies reporting differences between depressed patients and controls. However, these findings are variable and taken from relatively small studies often using suboptimal analytic approaches. The presented DTI study examined WM integrity in large samples of medication-free MDD patients (n=134) and healthy controls (n=54) using voxel-based morphometry (VBM) and tract-based spatial statistics (TBSS) approaches, and rigorous statistical thresholds. Compared with health control subjects, MDD patients show no significant differences in fractional anisotropy, radial diffusivity, mean diffusivity, and axonal diffusivity with either the VBM or the TBSS approach. Our findings suggest that disrupted WM integrity does not have a major role in the neurobiology of MDD in this relatively large study using optimal imaging acquisition and analysis; however, this does not eliminate the possibility that certain patient subgroups show WM disruption associated with depression.},\nauthor = {Choi, Ki Sueng and Holtzheimer, Paul E and Franco, Alexandre R and Kelley, Mary E and Dunlop, Boadie W and Hu, Xiaoping P and Mayberg, Helen S},\ndoi = {10.1038/npp.2013.345},\nfile = {:Users/10084029/Library/Application Support/Mendeley Desktop/Downloaded/Choi et al. - 2014 - Reconciling variable findings of white matter integrity in major depressive disorder.pdf:pdf},\nissn = {1740-634X},\njournal = {Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology},\nkeywords = {biological psychiatry,bipolar,clinical or preclinical,depression,diffusion tensor imaging,fractional anisotropy,imaging,magnetic resonance imaging,major depressive disorder,psychiatry {\\&} behavioral sciences,unipolar,white matter},\nmonth = {may},\nnumber = {6},\npages = {1332--9},\npmid = {24352368},\npublisher = {American College of Neuropsychopharmacology},\nshorttitle = {Neuropsychopharmacology},\ntitle = {{Reconciling variable findings of white matter integrity in major depressive disorder.}},\nurl = {http://dx.doi.org/10.1038/npp.2013.345},\nvolume = {39},\nyear = {2014}\n}\n

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\n \n\n \n \n \n \n \n \n Automated Methods for Hippocampus Segmentation: the Evolution and a Review of the State of the Art.\n \n \n \n \n\n\n \n Dill, V.; Franco, A. R.; and Pinho, M. S.\n\n\n \n\n\n\n Neuroinformatics. oct 2014.\n \n\n\n\n
\n\n\n\n \n \n $\"Automated$ Paper\n \n \n\n \n \n doi\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

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@article{Dill2014,\nauthor = {Dill, Vanderson and Franco, Alexandre Rosa and Pinho, M{\\'{a}}rcio Sarroglia},\ndoi = {10.1007/s12021-014-9243-4},\nfile = {:Users/10084029/Library/Application Support/Mendeley Desktop/Downloaded/Dill, Franco, Pinho - 2014 - Automated Methods for Hippocampus Segmentation the Evolution and a Review of the State of the Art.pdf:pdf},\nissn = {1539-2791},\njournal = {Neuroinformatics},\nkeywords = {alzheimer,evaluation of segmentation,hippocampus segmentation,images,imaging,magnetic resonance,medical,neuroimaging,s disease,segmentation methods},\nmonth = {oct},\ntitle = {{Automated Methods for Hippocampus Segmentation: the Evolution and a Review of the State of the Art}},\nurl = {http://link.springer.com/10.1007/s12021-014-9243-4},\nyear = {2014}\n}\n

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\n \n\n \n \n \n \n \n \n Default Mode, Executive Function, and Language Functional Connectivity Networks are Compromised in Mild Alzheimer´s Disease.\n \n \n \n \n\n\n \n Weiler, M.; Fukuda, A.; Massabki, L.; Lopes, T.; Franco, A.; Damasceno, B.; Cendes, F.; and Balthazar, M.\n\n\n \n\n\n\n Current Alzheimer Research, 11(3): 274–282. mar 2014.\n \n\n\n\n
\n\n\n\n \n \n $\"Default$ Paper\n \n \n\n \n \n doi\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

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@article{Weiler2014,\nauthor = {Weiler, Marina and Fukuda, Aya and Massabki, Lilian and Lopes, Tatila and Franco, Alexandre and Damasceno, Benito and Cendes, Fernando and Balthazar, Marcio},\ndoi = {10.2174/1567205011666140131114716},\nfile = {:Users/10084029/Library/Application Support/Mendeley Desktop/Downloaded/Weiler et al. - 2014 - Default Mode, Executive Function, and Language Functional Connectivity Networks are Compromised in Mild Alzheime.pdf:pdf},\nissn = {15672050},\njournal = {Current Alzheimer Research},\nkeywords = {alzheimer,cognition,default mode network,functional connectivity,functional networks,resting-state,s disease},\nmonth = {mar},\nnumber = {3},\npages = {274--282},\ntitle = {{Default Mode, Executive Function, and Language Functional Connectivity Networks are Compromised in Mild Alzheimer´s Disease}},\nurl = {http://www.eurekaselect.com/openurl/content.php?genre=article{\\&}issn=1567-2050{\\&}volume=11{\\&}issue=3{\\&}spage=274},\nvolume = {11},\nyear = {2014}\n}\n

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\n \n\n \n \n \n \n \n \n Whole cortical and default mode network mean functional connectivity as potential biomarkers for mild Alzheimer's disease.\n \n \n \n \n\n\n \n Balthazar, M. L. F.; de Campos, B. M.; Franco, A. R.; Damasceno, B. P.; and Cendes, F.\n\n\n \n\n\n\n Psychiatry research, 221(1): 37–42. jan 2014.\n \n\n\n\n
\n\n\n\n \n \n $\"Whole$ Paper\n \n \n\n \n \n doi\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

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@article{Balthazar2014,\nabstract = {The search for an Alzheimer's disease (AD) biomarker is one of the most relevant contemporary research topics due to the high prevalence and social costs of the disease. Functional connectivity (FC) of the default mode network (DMN) is a plausible candidate for such a biomarker. We evaluated 22 patients with mild AD and 26 age- and gender-matched healthy controls. All subjects underwent resting functional magnetic resonance imaging (fMRI) in a 3.0 T scanner. To identify the DMN, seed-based FC of the posterior cingulate was calculated. We also measured the sensitivity/specificity of the method, and verified a correlation with cognitive performance. We found a significant difference between patients with mild AD and controls in average z-scores: DMN, whole cortical positive (WCP) and absolute values. DMN individual values showed a sensitivity of 77.3{\\%} and specificity of 70{\\%}. DMN and WCP values were correlated to global cognition and episodic memory performance. We showed that individual measures of DMN connectivity could be considered a promising method to differentiate AD, even at an early phase, from normal aging. Further studies with larger numbers of participants, as well as validation of normal values, are needed for more definitive conclusions.},\nauthor = {Balthazar, Marcio Luiz Figueredo and de Campos, Brunno Machado and Franco, Alexandre Rosa and Damasceno, Benito Pereira and Cendes, Fernando},\ndoi = {10.1016/j.pscychresns.2013.10.010},\nfile = {:Users/10084029/Library/Application Support/Mendeley Desktop/Downloaded/Balthazar et al. - 2014 - Whole cortical and default mode network mean functional connectivity as potential biomarkers for mild Alzheime.pdf:pdf},\nissn = {1872-7123},\njournal = {Psychiatry research},\nkeywords = {Biomarker,Default mode network,Dementia,Resting state fMRI,default mode network},\nmonth = {jan},\nnumber = {1},\npages = {37--42},\npmid = {24268581},\npublisher = {Elsevier},\ntitle = {{Whole cortical and default mode network mean functional connectivity as potential biomarkers for mild Alzheimer's disease.}},\nurl = {http://www.ncbi.nlm.nih.gov/pubmed/24268581},\nvolume = {221},\nyear = {2014}\n}\n

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\n \n\n \n \n \n \n \n Dynamic Magnetic Resonance Imaging Phantom for Measuring the Stability of Functional Sequences.\n \n \n \n\n\n \n Capaverde, S.; Franco, A. R.; André, A.; Maria, A.; and Silva, M.\n\n\n \n\n\n\n In pages 5032, 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 \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

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@inproceedings{Capaverde2014,\nauthor = {Capaverde, Silva and Franco, Alexandre Rosa and Andr{\\'{e}}, Alessandro and Maria, Ana and Silva, Marques},\nfile = {:Users/10084029/Library/Application Support/Mendeley Desktop/Downloaded/Capaverde et al. - 2014 - Dynamic Magnetic Resonance Imaging Phantom for Measuring the Stability of Functional Sequences.pdf:pdf},\nkeywords = {Contrast-enhanced dynamic MRI,Functional image analysis,MR neuroimaging,alessandro andr{\\'{e}} mazzola e,alexandre da silva capaverde,alexandre rosa franco,amic magnetic resonance imaging,ana maria,phantom for measuring the,stability of functional sequences},\npages = {5032},\ntitle = {{Dynamic Magnetic Resonance Imaging Phantom for Measuring the Stability of Functional Sequences}},\nyear = {2014}\n}\n

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\n \n 2013\n \n \n (2)\n \n \n

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\n \n\n \n \n \n \n \n \n Toward a neuroimaging treatment selection biomarker for major depressive disorder.\n \n \n \n \n\n\n \n McGrath, C. L; Kelley, M. E; Holtzheimer, P. E; Dunlop, B. W; Craighead, W E.; Franco, A. R; Craddock, R C.; and Mayberg, H. S\n\n\n \n\n\n\n JAMA psychiatry (Chicago, Ill.), 70(8): 821–9. aug 2013.\n \n\n\n\n
\n\n\n\n \n \n $\"Toward$ Paper\n \n \n\n \n \n doi\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

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@article{McGrath2013,\nabstract = {IMPORTANCE: Currently, fewer than 40{\\%} of patients treated for major depressive disorder achieve remission with initial treatment. Identification of a biological marker that might improve these odds could have significant health and economic impact. OBJECTIVE: To identify a candidate neuroimaging "treatment-specific biomarker" that predicts differential outcome to either medication or psychotherapy. DESIGN: Brain glucose metabolism was measured with positron emission tomography prior to treatment randomization to either escitalopram oxalate or cognitive behavior therapy for 12 weeks. Patients who did not remit on completion of their phase 1 treatment were offered enrollment in phase 2 comprising an additional 12 weeks of treatment with combination escitalopram and cognitive behavior therapy. SETTING: Mood and anxiety disorders research program at an academic medical center. PARTICIPANTS: Men and women aged 18 to 60 years with currently untreated major depressive disorder. INTERVENTION: Randomized assignment to 12 weeks of treatment with either escitalopram oxalate (10-20 mg/d) or 16 sessions of manual-based cognitive behavior therapy. MAIN OUTCOME AND MEASURE: Remission, defined as a 17-item Hamilton depression rating scale score of 7 or less at both weeks 10 and 12, as assessed by raters blinded to treatment. RESULTS: Positive and negative predictors of remission were identified with a 2-way analysis of variance treatment (escitalopram or cognitive behavior therapy) × outcome (remission or nonresponse) interaction. Of 65 protocol completers, 38 patients with clear outcomes and usable positron emission tomography scans were included in the primary analysis: 12 remitters to cognitive behavior therapy, 11 remitters to escitalopram, 9 nonresponders to cognitive behavior therapy, and 6 nonresponders to escitalopram. Six limbic and cortical regions were identified, with the right anterior insula showing the most robust discriminant properties across groups (effect size = 1.43). Insula hypometabolism (relative to whole-brain mean) was associated with remission to cognitive behavior therapy and poor response to escitalopram, while insula hypermetabolism was associated with remission to escitalopram and poor response to cognitive behavior therapy. CONCLUSIONS AND RELEVANCE: If verified with prospective testing, the insula metabolism-based treatment-specific biomarker defined in this study provides the first objective marker, to our knowledge, to guide initial treatment selection for depression. TRIAL REGISTRATION: Registered at clinicaltrials.gov (NCT00367341).},\nauthor = {McGrath, Callie L and Kelley, Mary E and Holtzheimer, Paul E and Dunlop, Boadie W and Craighead, W Edward and Franco, Alexandre R and Craddock, R Cameron and Mayberg, Helen S},\ndoi = {10.1001/jamapsychiatry.2013.143},\nfile = {:Users/10084029/Library/Application Support/Mendeley Desktop/Downloaded/McGrath et al. - 2013 - Toward a neuroimaging treatment selection biomarker for major depressive disorder.pdf:pdf},\nissn = {2168-6238},\njournal = {JAMA psychiatry (Chicago, Ill.)},\nmonth = {aug},\nnumber = {8},\npages = {821--9},\npmid = {23760393},\ntitle = {{Toward a neuroimaging treatment selection biomarker for major depressive disorder.}},\nurl = {http://www.ncbi.nlm.nih.gov/pubmed/23760393},\nvolume = {70},\nyear = {2013}\n}\n

\n

\n\n\n

\n IMPORTANCE: Currently, fewer than 40% of patients treated for major depressive disorder achieve remission with initial treatment. Identification of a biological marker that might improve these odds could have significant health and economic impact. OBJECTIVE: To identify a candidate neuroimaging \"treatment-specific biomarker\" that predicts differential outcome to either medication or psychotherapy. DESIGN: Brain glucose metabolism was measured with positron emission tomography prior to treatment randomization to either escitalopram oxalate or cognitive behavior therapy for 12 weeks. Patients who did not remit on completion of their phase 1 treatment were offered enrollment in phase 2 comprising an additional 12 weeks of treatment with combination escitalopram and cognitive behavior therapy. SETTING: Mood and anxiety disorders research program at an academic medical center. PARTICIPANTS: Men and women aged 18 to 60 years with currently untreated major depressive disorder. INTERVENTION: Randomized assignment to 12 weeks of treatment with either escitalopram oxalate (10-20 mg/d) or 16 sessions of manual-based cognitive behavior therapy. MAIN OUTCOME AND MEASURE: Remission, defined as a 17-item Hamilton depression rating scale score of 7 or less at both weeks 10 and 12, as assessed by raters blinded to treatment. RESULTS: Positive and negative predictors of remission were identified with a 2-way analysis of variance treatment (escitalopram or cognitive behavior therapy) × outcome (remission or nonresponse) interaction. Of 65 protocol completers, 38 patients with clear outcomes and usable positron emission tomography scans were included in the primary analysis: 12 remitters to cognitive behavior therapy, 11 remitters to escitalopram, 9 nonresponders to cognitive behavior therapy, and 6 nonresponders to escitalopram. Six limbic and cortical regions were identified, with the right anterior insula showing the most robust discriminant properties across groups (effect size = 1.43). Insula hypometabolism (relative to whole-brain mean) was associated with remission to cognitive behavior therapy and poor response to escitalopram, while insula hypermetabolism was associated with remission to escitalopram and poor response to cognitive behavior therapy. CONCLUSIONS AND RELEVANCE: If verified with prospective testing, the insula metabolism-based treatment-specific biomarker defined in this study provides the first objective marker, to our knowledge, to guide initial treatment selection for depression. TRIAL REGISTRATION: Registered at clinicaltrials.gov (NCT00367341).\n

\n\n\n

\n \n\n \n \n \n \n \n \n Impact of analysis methods on the reproducibility and reliability of resting-state networks.\n \n \n \n \n\n\n \n Franco, A. R; Mannell, M. V; Calhoun, V. D; and Mayer, A. R\n\n\n \n\n\n\n Brain connectivity, 3(4): 363–74. jan 2013.\n \n\n\n\n
\n\n\n\n \n \n $\"Impact$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

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@article{Franco2013,\nabstract = {Though previous examinations of intrinsic resting-state networks (RSNs) in healthy populations have consistently identified several RSNs that represent connectivity patterns evoked by cognitive and sensory tasks, the effects of different analytic approaches on the reliability and reproducibility of these RSNs have yet to be fully explored. Thus, the primary aim of the current study was to investigate the effect of method (independent component analyses [ICA] vs. seed-based analyses) on RSN reproducibility (independent datasets) for ICA and reliability (independent time points) in both methods using functional magnetic resonance imaging. Good to excellent reproducibility was observed in 9 out of 10 commonly identified RSNs, indicating the robustness of these intrinsic fluctuations at the group level. Reliability analyses showed that results were dependent on three main methodological factors: (1) group versus subject-level analyses (group{\\textgreater}subject); (2) whether data from different visits were analyzed separately or jointly with ICA (combined{\\textgreater}separate ICA); and (3) whether ICA output was used to directly assess reliability or to inform seed-based analyses (seed-based{\\textgreater}ICA). These results suggest that variations in the analytic technique have a significant impact on individual reliability measurements, but do not significantly affect the reproducibility or reliability of RSNs at the group level. Further investigation into the effect of the analytic technique on RSN quantification is warranted to increase the utility of RSN analyses in clinical studies.},\nauthor = {Franco, Alexandre R and Mannell, Maggie V and Calhoun, Vince D and Mayer, Andrew R},\ndoi = {10.1089/brain.2012.0134},\nfile = {:Users/10084029/Library/Application Support/Mendeley Desktop/Downloaded/Franco et al. - 2013 - Impact of analysis methods on the reproducibility and reliability of resting-state networks.pdf:pdf},\nissn = {2158-0022},\njournal = {Brain connectivity},\nkeywords = {fmri,ica,reliability,reproducibility,resting state networks,seed-based},\nmonth = {jan},\nnumber = {4},\npages = {363--74},\npmid = {23705789},\ntitle = {{Impact of analysis methods on the reproducibility and reliability of resting-state networks.}},\nurl = {http://www.ncbi.nlm.nih.gov/pubmed/23705789},\nvolume = {3},\nyear = {2013}\n}\n

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\n \n 2012\n \n \n (2)\n \n \n

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\n \n\n \n \n \n \n \n \n Modeling conflict and error in the medial frontal cortex.\n \n \n \n \n\n\n \n Mayer, A. R; Teshiba, T. M; Franco, A. R; Ling, J.; Shane, M. S; Stephen, J. M; and Jung, R. E\n\n\n \n\n\n\n Human brain mapping, 33(12): 2843–55. dec 2012.\n \n\n\n\n
\n\n\n\n \n \n $\"Modeling$ Paper\n \n \n\n \n \n doi\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

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@article{Mayer2012,\nabstract = {Despite intensive study, the role of the dorsal medial frontal cortex (dMFC) in error monitoring and conflict processing remains actively debated. The current experiment manipulated conflict type (stimulus conflict only or stimulus and response selection conflict) and utilized a novel modeling approach to isolate error and conflict variance during a multimodal numeric Stroop task. Specifically, hemodynamic response functions resulting from two statistical models that either included or isolated variance arising from relatively few error trials were directly contrasted. Twenty-four participants completed the task while undergoing event-related functional magnetic resonance imaging on a 1.5-Tesla scanner. Response times monotonically increased based on the presence of pure stimulus or stimulus and response selection conflict. Functional results indicated that dMFC activity was present during trials requiring response selection and inhibition of competing motor responses, but absent during trials involving pure stimulus conflict. A comparison of the different statistical models suggested that relatively few error trials contributed to a disproportionate amount of variance (i.e., activity) throughout the dMFC, but particularly within the rostral anterior cingulate gyrus (rACC). Finally, functional connectivity analyses indicated that an empirically derived seed in the dorsal ACC/pre-SMA exhibited strong connectivity (i.e., positive correlation) with prefrontal and inferior parietal cortex but was anti-correlated with the default-mode network. An empirically derived seed from the rACC exhibited the opposite pattern, suggesting that sub-regions of the dMFC exhibit different connectivity patterns with other large scale networks implicated in internal mentations such as daydreaming (default-mode) versus the execution of top-down attentional control (fronto-parietal). Hum Brain Mapp, 2012. {\\textcopyright} 2011 Wiley Periodicals, Inc.},\nauthor = {Mayer, Andrew R and Teshiba, Terri M and Franco, Alexandre R and Ling, Josef and Shane, Matthew S and Stephen, Julia M and Jung, Rex E},\ndoi = {10.1002/hbm.21405},\nfile = {:Users/10084029/Library/Application Support/Mendeley Desktop/Downloaded/Mayer et al. - 2012 - Modeling conflict and error in the medial frontal cortex.pdf:pdf},\nissn = {1097-0193},\njournal = {Human brain mapping},\nkeywords = {conflict,error,fmri,multimodal,selective attention},\nmonth = {dec},\nnumber = {12},\npages = {2843--55},\npmid = {21976411},\ntitle = {{Modeling conflict and error in the medial frontal cortex.}},\nurl = {http://www.ncbi.nlm.nih.gov/pubmed/21976411},\nvolume = {33},\nyear = {2012}\n}\n

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\n \n\n \n \n \n \n \n \n The Illness Density Index (IDI) : A longitudinal measure of treatment efficacy.\n \n \n \n \n\n\n \n Kelley, M. E; Franco, A. R; Mayberg, H. S; and Holtzheimer, P. E\n\n\n \n\n\n\n Clinical trials (London, England), (July). jul 2012.\n \n\n\n\n
\n\n\n\n \n \n $\"The$ Paper\n \n \n\n \n \n doi\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

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@article{Kelley2012,\nabstract = {BACKGROUND: A reliable and meaningful quantitative index of success is paramount in the trial of any new treatment. However, existing methods for defining response and remission for treatments tested for psychiatric disorders are limited in that they often minimize the variance in change over time among individual patients and generally use arbitrarily chosen levels of functioning at specified times during treatment. PURPOSE: To suggest and determine the properties of an alternative measure of treatment success, the Illness Density Index (IDI), that may be more sensitive to fluctuations in symptoms over the course of treatment compared to existing measures. METHODS: We examined data from 64 depressed patients with multiple assessments of the Hamilton Depression Rating Scale (HDRS) over 12 weeks of randomized treatment in order to compare and contrast varying numerical definitions of response and remission, including percent change and linear slope over time. RESULTS: Examination of the indices comparing the within-sample rank of individual patients revealed that these indices agree in cases where patients have little or no response as well as clear and sustained response, while they differ in patients who have a slow (or late) response as well as relapse during the treatment course. LIMITATIONS: The measure may not be useful for all types of studies, especially short-term treatment trials. CONCLUSIONS: The IDI is highly correlated with both categorical (e.g., remission) and continuous (e.g., percent change) definitions of treatment success. Furthermore, it differentiates certain trajectories of change that current definitions do not. Thus, the proposed index may be a valuable addition to current measures of efficacy, especially when trying to identify biological substrates of illness or predictors of long-term outcome. Clinical Trials 2012; 0: 1-9. http://ctj.sagepub.com.},\nauthor = {Kelley, Mary E and Franco, Alexandre R and Mayberg, Helen S and Holtzheimer, Paul E},\ndoi = {10.1177/1740774512450099},\nfile = {:Users/10084029/Library/Application Support/Mendeley Desktop/Downloaded/Kelley et al. - 2012 - The Illness Density Index (IDI) A longitudinal measure of treatment efficacy.pdf:pdf},\nissn = {1740-7753},\njournal = {Clinical trials (London, England)},\nmonth = {jul},\nnumber = {July},\npmid = {22801557},\ntitle = {{The Illness Density Index (IDI) : A longitudinal measure of treatment efficacy.}},\nurl = {http://www.ncbi.nlm.nih.gov/pubmed/22801557},\nyear = {2012}\n}\n

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\n \n 2010\n \n \n (1)\n \n \n

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\n \n\n \n \n \n \n \n Resting state and task-induced deactivation: A methodological comparison in patients with schizophrenia and healthy controls.\n \n \n \n\n\n \n Mannell, M. V.; Franco, A. R.; Calhoun, V. D.; Cañive, J. M.; Thoma, R. J.; and Mayer, A. R.\n\n\n \n\n\n\n Human Brain Mapping, 31(3): 424–437. 2010.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\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

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@article{Mannell2010,\nabstract = {Changes in the default mode network (DMN) have been linked to multiple neurological disorders including schizophrenia. The anticorrelated relationship the DMN shares with task-related networks permits the quantification of this network both during task (task-induced deactivations: TID) and during periods of passive mental activity (extended rest). However, the effects of different methodologies (TID vs. extended rest) for quantifying the DMN in the same clinical population are currently not well understood. Moreover, several different analytic techniques, including independent component analyses (ICA) and seed-based correlation analyses, exist for examining functional connectivity during extended resting states. The current study compared both methodologies and analytic techniques in a group of patients with schizophrenia (SP) and matched healthy controls. Results indicated that TID analyses, ICA, and seed-based correlation all consistently identified the midline (anterior and posterior cingulate gyrus) and lateral parietal cortex as core regions of the DMN, as well as more variable involvement of temporal lobe structures. In addition, SP exhibited increased deactivation during task, as well as decreased functional connectivity with frontal regions and increased connectivity with posterior and subcortical areas during periods of extended rest. The increased posterior and reduced anterior connectivity may partially explain some of the cognitive dysfunction and clinical symptoms that are frequently associated with schizophrenia.},\nauthor = {Mannell, Maggie V. and Franco, Alexandre R. and Calhoun, Vince D. and Ca{\\~{n}}ive, Jose M. and Thoma, Robert J. and Mayer, Andrew R.},\ndoi = {10.1002/hbm.20876},\nfile = {:Users/10084029/Library/Application Support/Mendeley Desktop/Downloaded/Mannell et al. - 2010 - Resting state and task-induced deactivation A methodological comparison in patients with schizophrenia and he(2).pdf:pdf},\nisbn = {5052720769},\nissn = {10659471},\njournal = {Human Brain Mapping},\nkeywords = {Connectivity,Deactivation,Default-mode network,Independent component analysis,Schizophrenia,fMRI},\nnumber = {3},\npages = {424--437},\npmid = {19777578},\ntitle = {{Resting state and task-induced deactivation: A methodological comparison in patients with schizophrenia and healthy controls}},\nvolume = {31},\nyear = {2010}\n}\n

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\n \n 2009\n \n \n (4)\n \n \n

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\n \n\n \n \n \n \n \n \n The neural networks underlying auditory sensory gating.\n \n \n \n \n\n\n \n Mayer, a R; Hanlon, F M; Franco, a R; Teshiba, T M; Thoma, R J; Clark, V P; and Canive, J M\n\n\n \n\n\n\n NeuroImage, 44(1): 182–9. jan 2009.\n \n\n\n\n
\n\n\n\n \n \n $\"The$ Paper\n \n \n\n \n \n doi\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

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@article{Mayer2009,\nabstract = {One of the most consistent electrophysiological deficits reported in the schizophrenia literature is the failure to inhibit, or properly gate, the neuronal response to the second stimulus of an identical pair (i.e., sensory gating). Although animal and invasive human studies have consistently implicated the auditory cortex, prefrontal cortex and hippocampus in mediating the sensory gating response, localized activation in these structures has not always been reported during non-invasive imaging modalities. In the current experiment, event-related FMRI and a variant of the traditional gating paradigm were utilized to examine how the gating network differentially responded to the processing of pairs of identical and non-identical tones. Two single-tone conditions were also presented so that they could be used to estimate the HRF for paired stimuli, reconstructed based on actual hemodynamic responses, to serve as a control non-gating condition. Results supported an emerging theory that the gating response for both paired-tone conditions was primarily mediated by auditory and prefrontal cortex, with potential contributions from the thalamus. Results also indicated that the left auditory cortex may play a preferential role in determining the stimuli that should be inhibited (gated) or receive further processing due to novelty of information. In contrast, there was no evidence of hippocampal involvement, suggesting that future work is needed to determine what role it may play in the gating response.},\nauthor = {Mayer, a R and Hanlon, F M and Franco, a R and Teshiba, T M and Thoma, R J and Clark, V P and Canive, J M},\ndoi = {10.1016/j.neuroimage.2008.08.025},\nfile = {:Users/10084029/Library/Application Support/Mendeley Desktop/Downloaded/Mayer et al. - 2009 - The neural networks underlying auditory sensory gating.pdf:pdf},\nissn = {1095-9572},\njournal = {NeuroImage},\nkeywords = {Adult,Auditory Perception,Auditory Perception: physiology,Brain,Brain Mapping,Brain: physiology,Female,Humans,Image Processing, Computer-Assisted,Magnetic Resonance Imaging,Male,Nerve Net,Nerve Net: physiology,Sensory Gating,Sensory Gating: physiology},\nmonth = {jan},\nnumber = {1},\npages = {182--9},\npmid = {18801443},\npublisher = {Elsevier Inc.},\ntitle = {{The neural networks underlying auditory sensory gating.}},\nurl = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2656944{\\&}tool=pmcentrez{\\&}rendertype=abstract},\nvolume = {44},\nyear = {2009}\n}\n

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\n \n\n \n \n \n \n \n \n Interrater and intermethod reliability of default mode network selection.\n \n \n \n \n\n\n \n Franco, A. R; Pritchard, A.; Calhoun, V. D; and Mayer, A. R\n\n\n \n\n\n\n Human brain mapping, 30(7): 2293–303. jul 2009.\n \n\n\n\n
\n\n\n\n \n \n $\"Interrater$ Paper\n \n \n\n \n \n doi\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

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@article{Franco2009,\nabstract = {There has been a growing interest in the neuroimaging community regarding resting state data (i.e., passive mental activity) and the subsequent activation of the so-called default mode network (DMN). Although this network was originally characterized by a pattern of deactivation during active cognitive states, more recent applications of data-driven techniques such as independent component analysis (ICA) have permitted the analysis of brain activation during extended periods of truly passive mental activity. However, ICA requires the resultant components to be evaluated for "goodness of fit" via either human raters or more automated techniques. To our knowledge, an investigation on the reliability of either technique in determining the component that best corresponds to default-mode activity has not been performed. Moreover, it is not clear how automated techniques, which are necessarily dependent upon a template mask, are affected by the structures used to compose the mask. The current study investigated both interrater (human-human) reliability and intermethod (human-machine) reliability for determining DMN activation in 42 healthy controls. Results indicated that near perfect interrater reliability was achieved, whereas intermethod reliability was only within the moderate range. The latter was significantly improved via a weighted combination of the anterior and posterior cingulate nodes of the DMN. Implications for fully automating the component selection process are discussed.},\nauthor = {Franco, Alexandre R and Pritchard, Aaron and Calhoun, Vince D and Mayer, Andrew R},\ndoi = {10.1002/hbm.20668},\nfile = {:Users/10084029/Library/Application Support/Mendeley Desktop/Downloaded/Franco et al. - 2009 - Interrater and intermethod reliability of default mode network selection.pdf:pdf},\nissn = {1097-0193},\njournal = {Human brain mapping},\nkeywords = {Adult,Analysis of Variance,Automatic Data Processing,Brain,Brain Mapping,Brain Mapping: methods,Brain: physiology,Female,Humans,Image Processing, Computer-Assisted,Image Processing, Computer-Assisted: methods,Magnetic Resonance Imaging,Male,Mental Processes,Mental Processes: physiology,Reproducibility of Results},\nmonth = {jul},\nnumber = {7},\npages = {2293--303},\npmid = {19206103},\ntitle = {{Interrater and intermethod reliability of default mode network selection.}},\nurl = {http://www.ncbi.nlm.nih.gov/pubmed/19206103},\nvolume = {30},\nyear = {2009}\n}\n

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\n \n\n \n \n \n \n \n \n Neuronal modulation of auditory attention by informative and uninformative spatial cues.\n \n \n \n \n\n\n \n Mayer, A. R; Franco, A. R; and Harrington, D. L\n\n\n \n\n\n\n Human brain mapping, 30(5): 1652–66. may 2009.\n \n\n\n\n
\n\n\n\n \n \n $\"Neuronal$ Paper\n \n \n\n \n \n doi\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 \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

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@article{Mayer2009a,\nabstract = {Sounds provide important information about the spatial environment, including the location of approaching objects. Attention to sounds can be directed through automatic or more controlled processes, which have been well studied in the visual modality. However, little is known about the neural underpinnings of attentional control mechanisms for auditory signals. We studied healthy adults who underwent event-related FMRI while performing a task that manipulated automatic and more controlled auditory orienting by varying the probability that cues correctly predicted target location. Specifically, we examined the effects of uninformative (50{\\%} validity ratio) and informative (75{\\%} validity ratio) auditory cues on reaction time (RT) and neuronal functioning. The stimulus-onset asynchrony (SOA) between the cue and the target was either 100 or 800 ms. At the 100 ms SOA, RT was faster for valid than invalid trials for both cue types, and frontoparietal activation was greater for invalid than valid trials. At the 800 ms SOA, RT and functional activation depended on whether cues were informative or uninformative, and whether cues correctly or incorrectly predicted the target location. Contrary to our prediction, activation in a frontoparietal network was greater for uninformative than informative cues across several different comparisons and at both SOAs. This finding contrasts with similar research of visual orienting, and suggests that the auditory modality may be more biased toward automatic shifts of attention following uninformative cues.},\nauthor = {Mayer, Andrew R and Franco, Alexandre R and Harrington, Deborah L},\ndoi = {10.1002/hbm.20631},\nfile = {:Users/10084029/Library/Application Support/Mendeley Desktop/Downloaded/Mayer, Franco, Harrington - 2009 - Neuronal modulation of auditory attention by informative and uninformative spatial cues.pdf:pdf},\nissn = {1097-0193},\njournal = {Human brain mapping},\nkeywords = {Adult,Analysis of Variance,Attention,Attention: physiology,Auditory Cortex,Auditory Cortex: blood supply,Auditory Cortex: physiology,Auditory Perception,Auditory Perception: physiology,Brain Mapping,Cues,Female,Functional Laterality,Humans,Image Processing, Computer-Assisted,Image Processing, Computer-Assisted: methods,Magnetic Resonance Imaging,Male,Oxygen,Oxygen: blood,Reaction Time,Reaction Time: physiology,Signal Detection, Psychological,Signal Detection, Psychological: physiology,Space Perception,Space Perception: physiology,Young Adult},\nmonth = {may},\nnumber = {5},\npages = {1652--66},\npmid = {18661505},\ntitle = {{Neuronal modulation of auditory attention by informative and uninformative spatial cues.}},\nurl = {http://www.ncbi.nlm.nih.gov/pubmed/18661505},\nvolume = {30},\nyear = {2009}\n}\n

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\n \n\n \n \n \n \n \n \n The effects of stimulus modality and frequency of stimulus presentation on cross-modal distraction.\n \n \n \n \n\n\n \n Mayer, A. R; Franco, A. R; Canive, J; and Harrington, D. L\n\n\n \n\n\n\n Cerebral Cortex, 19(5): 993–1007. 2009.\n \n\n\n\n
\n\n\n\n \n \n $\"The$ Paper\n \n \n\n \n \n doi\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\n\n\n

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@article{Mayer2009b,\nabstract = {Selective attention produces enhanced activity (attention-related modulations [ARMs]) in cortical regions corresponding to the attended modality and suppressed activity in cortical regions corresponding to the ignored modality. However, effects of behavioral context (e.g., temporal vs. spatial tasks) and basic stimulus properties (i.e., stimulus frequency) on ARMs are not fully understood. The current study used functional magnetic resonance imaging to investigate selectively attending and responding to either a visual or auditory metronome in the presence of asynchronous cross-modal distractors of 3 different frequencies (0.5, 1, and 2 Hz). Attending to auditory information while ignoring visual distractors was generally more efficient (i.e., required coordination of a smaller network) and less effortful (i.e., decreased interference and presence of ARMs) than attending to visual information while ignoring auditory distractors. However, these effects were modulated by stimulus frequency, as attempting to ignore auditory information resulted in the obligatory recruitment of auditory cortical areas during infrequent (0.5 Hz) stimulation. Robust ARMs were observed in both visual and auditory cortical areas at higher frequencies (2 Hz), indicating that participants effectively allocated attention to more rapidly presented targets. In summary, results provide neuroanatomical correlates for the dominance of the auditory modality in behavioral contexts that are highly dependent on temporal processing.},\nauthor = {Mayer, Andrew R and Franco, Alexandre R and Canive, J and Harrington, Deborah L},\ndoi = {10.1093/cercor/bhn148},\nfile = {:Users/10084029/Library/Application Support/Mendeley Desktop/Downloaded/Mayer et al. - 2009 - The effects of stimulus modality and frequency of stimulus presentation on cross-modal distraction(2).pdf:pdf},\nissn = {1460-2199},\njournal = {Cerebral Cortex},\nkeywords = {Acoustic Stimulation,Adult,Attention,Attention: physiology,Auditory Cortex,Auditory Cortex: physiology,Auditory Perception,Auditory Perception: physiology,Female,Gyrus Cinguli,Gyrus Cinguli: physiology,Humans,Magnetic Resonance Imaging,Male,Perceptual Masking,Perceptual Masking: physiology,Photic Stimulation,Psychomotor Performance,Psychomotor Performance: physiology,Visual Cortex,Visual Cortex: physiology,Visual Perception,Visual Perception: physiology},\nnumber = {5},\npages = {993--1007},\npmid = {18787235},\ntitle = {{The effects of stimulus modality and frequency of stimulus presentation on cross-modal distraction.}},\nurl = {http://www.ncbi.nlm.nih.gov/pubmed/18787235},\nvolume = {19},\nyear = {2009}\n}\n

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\n \n 2008\n \n \n (1)\n \n \n

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\n \n\n \n \n \n \n \n \n Multimodal and Multi-tissue Measures of Connectivity Revealed by Joint Independent Component Analysis.\n \n \n \n \n\n\n \n Franco, A. R; Ling, J.; Caprihan, A.; Calhoun, V. D; Jung, R. E; Heileman, G. L; and Mayer, A. R\n\n\n \n\n\n\n IEEE journal of selected topics in signal processing, 2(6): 986–997. dec 2008.\n \n\n\n\n
\n\n\n\n \n \n $\"Multimodal$ Paper\n \n \n\n \n \n doi\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

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@article{Franco2008,\nabstract = {The human brain functions as an efficient system where signals arising from gray matter are transported via white matter tracts to other regions of the brain to facilitate human behavior. However, with a few exceptions, functional and structural neuroimaging data are typically optimized to maximize the quantification of signals arising from a single source. For example, functional magnetic resonance imaging (FMRI) is typically used as an index of gray matter functioning whereas diffusion tensor imaging (DTI) is typically used to determine white matter properties. While it is likely that these signals arising from different tissue sources contain complementary information, the signal processing algorithms necessary for the fusion of neuroimaging data across imaging modalities are still in a nascent stage. In the current paper we present a data-driven method for combining measures of functional connectivity arising from gray matter sources (FMRI resting state data) with different measures of white matter connectivity (DTI). Specifically, a joint independent component analysis (J-ICA) was used to combine these measures of functional connectivity following intensive signal processing and feature extraction within each of the individual modalities. Our results indicate that one of the most predominantly used measures of functional connectivity (activity in the default mode network) is highly dependent on the integrity of white matter connections between the two hemispheres (corpus callosum) and within the cingulate bundles. Importantly, the discovery of this complex relationship of connectivity was entirely facilitated by the signal processing and fusion techniques presented herein and could not have been revealed through separate analyses of both data types as is typically performed in the majority of neuroimaging experiments. We conclude by discussing future applications of this technique to other areas of neuroimaging and examining potential limitations of the methods.},\nauthor = {Franco, Alexandre R and Ling, Josef and Caprihan, Arvind and Calhoun, Vince D and Jung, Rex E and Heileman, Gregory L and Mayer, Andrew R},\ndoi = {10.1109/JSTSP.2008.2006718},\nfile = {:Users/10084029/Library/Application Support/Mendeley Desktop/Downloaded/Franco et al. - 2008 - Multimodal and Multi-tissue Measures of Connectivity Revealed by Joint Independent Component Analysis.pdf:pdf},\nissn = {1941-0484},\njournal = {IEEE journal of selected topics in signal processing},\nmonth = {dec},\nnumber = {6},\npages = {986--997},\npmid = {19777078},\ntitle = {{Multimodal and Multi-tissue Measures of Connectivity Revealed by Joint Independent Component Analysis.}},\nurl = {http://www.ncbi.nlm.nih.gov/pubmed/19777078},\nvolume = {2},\nyear = {2008}\n}\n

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\n The human brain functions as an efficient system where signals arising from gray matter are transported via white matter tracts to other regions of the brain to facilitate human behavior. However, with a few exceptions, functional and structural neuroimaging data are typically optimized to maximize the quantification of signals arising from a single source. For example, functional magnetic resonance imaging (FMRI) is typically used as an index of gray matter functioning whereas diffusion tensor imaging (DTI) is typically used to determine white matter properties. While it is likely that these signals arising from different tissue sources contain complementary information, the signal processing algorithms necessary for the fusion of neuroimaging data across imaging modalities are still in a nascent stage. In the current paper we present a data-driven method for combining measures of functional connectivity arising from gray matter sources (FMRI resting state data) with different measures of white matter connectivity (DTI). Specifically, a joint independent component analysis (J-ICA) was used to combine these measures of functional connectivity following intensive signal processing and feature extraction within each of the individual modalities. Our results indicate that one of the most predominantly used measures of functional connectivity (activity in the default mode network) is highly dependent on the integrity of white matter connections between the two hemispheres (corpus callosum) and within the cingulate bundles. Importantly, the discovery of this complex relationship of connectivity was entirely facilitated by the signal processing and fusion techniques presented herein and could not have been revealed through separate analyses of both data types as is typically performed in the majority of neuroimaging experiments. We conclude by discussing future applications of this technique to other areas of neuroimaging and examining potential limitations of the methods.\n

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\n \n\n \n \n \n \n \n \n Assessment and quantification of head motion in neuropsychiatric functional imaging research as applied to schizophrenia.\n \n \n \n \n\n\n \n Mayer, A.; Franco, A.; Ling, J.; and CaNIve, J.\n\n\n \n\n\n\n Journal of the International Neuropsychological Society, 13(05): 839–845. 2007.\n \n\n\n\n
\n\n\n\n \n \n $\"Assessment$ 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

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@article{Mayer2007,\nauthor = {Mayer, A.R. and Franco, A.R. and Ling, Josef and CaNIve, J.M.},\nissn = {1355-6177},\njournal = {Journal of the International Neuropsychological Society},\nkeywords = {artifact,f mri,motion,neuropsychiatric,quality assurance,schizophrenia},\nnumber = {05},\npages = {839--845},\npublisher = {Cambridge Univ Press},\ntitle = {{Assessment and quantification of head motion in neuropsychiatric functional imaging research as applied to schizophrenia}},\nurl = {http://journals.cambridge.org/abstract{\\_}S1355617707071081},\nvolume = {13},\nyear = {2007}\n}\n

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