@Article{Fiser2001,
  author   = {J Fiser and Richard N Aslin},
  journal  = {Psychol Sci},
  title    = {Unsupervised statistical learning of higher-order spatial structures from visual scenes.},
  year     = {2001},
  number   = {6},
  pages    = {499-504},
  volume   = {12},
  abstract = {Three experiments investigated the ability of human observers to extract
	the joint and conditional probabilities of shape co-occurrences during
	passive viewing of complex visual scenes. Results indicated that
	statistical learning of shape conjunctions was both rapid and automatic,
	as subjects were not instructed to attend to any particularfeatures
	of the displays. Moreover, in addition to single-shape frequency,
	subjects acquired in parallel several different higher-order aspects
	of the statistical structure of the displays, including absolute
	shape-position relations in an array, shape-pair arrangements independent
	of position, and conditional probabilities of shape co-occurrences.
	Unsupervised learning of these higher-order statistics provides support
	for Barlow's theory of visual recognition, which posits that detecting
	"suspicious coincidences" of elements during recognition is a necessary
	prerequisite for efficient learning of new visual features.},
  keywords = {Computing Methodologies, Human, Language, Learning, Mental Processes, Models, Theoretical, Stochastic Processes, Support, U.S. Gov't, Non-P.H.S., Cognition, Linguistics, Neural Networks (Computer), Practice (Psychology), Non-U.S. Gov't, Memory, Psychological, Task Performance and Analysis, Time Factors, Visual Perception, Adult, Attention, Discrimination Learning, Female, Male, Short-Term, Mental Recall, Orientation, Pattern Recognition, Visual, Perceptual Masking, Reading, Concept Formation, Form Perception, Animals, Corpus Striatum, Shrews, P.H.S., Visual Cortex, Visual Pathways, Acoustic Stimulation, Auditory Cortex, Auditory Perception, Cochlea, Ear, Gerbillinae, Glycine, Hearing, Neurons, Space Perception, Strychnine, Adolescent, Decision Making, Reaction Time, Astrocytoma, Brain Mapping, Brain Neoplasms, Cerebral Cortex, Electric Stimulation, Electrophysiology, Epilepsy, Temporal Lobe, Evoked Potentials, Frontal Lobe, Noise, Parietal Lobe, Scalp, Child, Language Development, Psycholinguistics, Brain, Perception, Speech, Vocalization, Animal, Discrimination (Psychology), Hippocampus, Rats, Calcium, Chelating Agents, Excitatory Postsynaptic Potentials, Glutamic Acid, Guanosine Diphosphate, In Vitro, Neuronal Plasticity, Pyramidal Cells, Receptors, AMPA, Metabotropic Glutamate, N-Methyl-D-Aspartate, Somatosensory Cortex, Synapses, Synaptic Transmission, Thionucleotides, Action Potentials, Calcium Channels, L-Type, Electric Conductivity, Entorhinal Cortex, Neurological, Long-Evans, Infant, Mathematics, Statistics, Probability Learning, Problem Solving, Psychophysics, 11760138},
}

{"_id":"54PvtaTm3dJDA92pp","bibbaseid":"fiser-aslin-unsupervisedstatisticallearningofhigherorderspatialstructuresfromvisualscenes-2001","authorIDs":[],"author_short":["Fiser, J","Aslin, R. N"],"bibdata":{"bibtype":"article","type":"article","author":[{"firstnames":["J"],"propositions":[],"lastnames":["Fiser"],"suffixes":[]},{"firstnames":["Richard","N"],"propositions":[],"lastnames":["Aslin"],"suffixes":[]}],"journal":"Psychol Sci","title":"Unsupervised statistical learning of higher-order spatial structures from visual scenes.","year":"2001","number":"6","pages":"499-504","volume":"12","abstract":"Three experiments investigated the ability of human observers to extract the joint and conditional probabilities of shape co-occurrences during passive viewing of complex visual scenes. Results indicated that statistical learning of shape conjunctions was both rapid and automatic, as subjects were not instructed to attend to any particularfeatures of the displays. Moreover, in addition to single-shape frequency, subjects acquired in parallel several different higher-order aspects of the statistical structure of the displays, including absolute shape-position relations in an array, shape-pair arrangements independent of position, and conditional probabilities of shape co-occurrences. Unsupervised learning of these higher-order statistics provides support for Barlow's theory of visual recognition, which posits that detecting \"suspicious coincidences\" of elements during recognition is a necessary prerequisite for efficient learning of new visual features.","keywords":"Computing Methodologies, Human, Language, Learning, Mental Processes, Models, Theoretical, Stochastic Processes, Support, U.S. Gov't, Non-P.H.S., Cognition, Linguistics, Neural Networks (Computer), Practice (Psychology), Non-U.S. Gov't, Memory, Psychological, Task Performance and Analysis, Time Factors, Visual Perception, Adult, Attention, Discrimination Learning, Female, Male, Short-Term, Mental Recall, Orientation, Pattern Recognition, Visual, Perceptual Masking, Reading, Concept Formation, Form Perception, Animals, Corpus Striatum, Shrews, P.H.S., Visual Cortex, Visual Pathways, Acoustic Stimulation, Auditory Cortex, Auditory Perception, Cochlea, Ear, Gerbillinae, Glycine, Hearing, Neurons, Space Perception, Strychnine, Adolescent, Decision Making, Reaction Time, Astrocytoma, Brain Mapping, Brain Neoplasms, Cerebral Cortex, Electric Stimulation, Electrophysiology, Epilepsy, Temporal Lobe, Evoked Potentials, Frontal Lobe, Noise, Parietal Lobe, Scalp, Child, Language Development, Psycholinguistics, Brain, Perception, Speech, Vocalization, Animal, Discrimination (Psychology), Hippocampus, Rats, Calcium, Chelating Agents, Excitatory Postsynaptic Potentials, Glutamic Acid, Guanosine Diphosphate, In Vitro, Neuronal Plasticity, Pyramidal Cells, Receptors, AMPA, Metabotropic Glutamate, N-Methyl-D-Aspartate, Somatosensory Cortex, Synapses, Synaptic Transmission, Thionucleotides, Action Potentials, Calcium Channels, L-Type, Electric Conductivity, Entorhinal Cortex, Neurological, Long-Evans, Infant, Mathematics, Statistics, Probability Learning, Problem Solving, Psychophysics, 11760138","bibtex":"@Article{Fiser2001,\n author = {J Fiser and Richard N Aslin},\n journal = {Psychol Sci},\n title = {Unsupervised statistical learning of higher-order spatial structures from visual scenes.},\n year = {2001},\n number = {6},\n pages = {499-504},\n volume = {12},\n abstract = {Three experiments investigated the ability of human observers to extract\n\tthe joint and conditional probabilities of shape co-occurrences during\n\tpassive viewing of complex visual scenes. Results indicated that\n\tstatistical learning of shape conjunctions was both rapid and automatic,\n\tas subjects were not instructed to attend to any particularfeatures\n\tof the displays. Moreover, in addition to single-shape frequency,\n\tsubjects acquired in parallel several different higher-order aspects\n\tof the statistical structure of the displays, including absolute\n\tshape-position relations in an array, shape-pair arrangements independent\n\tof position, and conditional probabilities of shape co-occurrences.\n\tUnsupervised learning of these higher-order statistics provides support\n\tfor Barlow's theory of visual recognition, which posits that detecting\n\t\"suspicious coincidences\" of elements during recognition is a necessary\n\tprerequisite for efficient learning of new visual features.},\n keywords = {Computing Methodologies, Human, Language, Learning, Mental Processes, Models, Theoretical, Stochastic Processes, Support, U.S. Gov't, Non-P.H.S., Cognition, Linguistics, Neural Networks (Computer), Practice (Psychology), Non-U.S. Gov't, Memory, Psychological, Task Performance and Analysis, Time Factors, Visual Perception, Adult, Attention, Discrimination Learning, Female, Male, Short-Term, Mental Recall, Orientation, Pattern Recognition, Visual, Perceptual Masking, Reading, Concept Formation, Form Perception, Animals, Corpus Striatum, Shrews, P.H.S., Visual Cortex, Visual Pathways, Acoustic Stimulation, Auditory Cortex, Auditory Perception, Cochlea, Ear, Gerbillinae, Glycine, Hearing, Neurons, Space Perception, Strychnine, Adolescent, Decision Making, Reaction Time, Astrocytoma, Brain Mapping, Brain Neoplasms, Cerebral Cortex, Electric Stimulation, Electrophysiology, Epilepsy, Temporal Lobe, Evoked Potentials, Frontal Lobe, Noise, Parietal Lobe, Scalp, Child, Language Development, Psycholinguistics, Brain, Perception, Speech, Vocalization, Animal, Discrimination (Psychology), Hippocampus, Rats, Calcium, Chelating Agents, Excitatory Postsynaptic Potentials, Glutamic Acid, Guanosine Diphosphate, In Vitro, Neuronal Plasticity, Pyramidal Cells, Receptors, AMPA, Metabotropic Glutamate, N-Methyl-D-Aspartate, Somatosensory Cortex, Synapses, Synaptic Transmission, Thionucleotides, Action Potentials, Calcium Channels, L-Type, Electric Conductivity, Entorhinal Cortex, Neurological, Long-Evans, Infant, Mathematics, Statistics, Probability Learning, Problem Solving, Psychophysics, 11760138},\n}\n\n","author_short":["Fiser, J","Aslin, R. 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