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Learning Predictive Statistics: Strategies and Brain Mechanisms
Wang, Rui1,2; Shen, Yuan3,4; Tino, Peter4; Welchman, Andrew E.2; Kourtzi, Zoe2
2017-08-30
Source PublicationJOURNAL OF NEUROSCIENCE
Correspondent Emailzk240@cam.ac.uk.
ISSN0270-6474
SubtypeArticle
Volume37Issue:35Pages:8412-8427
Abstract

When immersed in a new environment, we are challenged to decipher initially incomprehensible streams of sensory information. However, quite rapidly, the brain finds structure and meaning in these incoming signals, helping us to predict and prepare ourselves for future actions. This skill relies on extracting the statistics of event streams in the environment that contain regularities of variable complexity from simple repetitive patterns to complex probabilistic combinations. Here, we test the brain mechanisms that mediate our ability to adapt to the environment's statistics and predict upcoming events. By combining behavioral training and multisession fMRI in human participants (male and female), we track the corticostriatal mechanisms that mediate learning of temporal sequences as they change in structure complexity. We show that learning of predictive structures relates to individual decision strategy; that is, selecting the most probable outcome in a given context (maximizing) versus matching the exact sequence statistics. These strategies engage distinct human brain regions: maximizing engages dorsolateral prefrontal, cingulate, sensory-motor regions, and basal ganglia (dorsal caudate, putamen), whereas matching engages occipitotemporal regions (including the hippocampus) and basal ganglia (ventral caudate). Our findings provide evidence for distinct corticostriatal mechanisms that facilitate our ability to extract behaviorally relevant statistics to make predictions.

KeywordfMRI learning prediction vision
DOI10.1523/JNEUROSCI.0144-17.2017
Indexed BySCI ; SSCI
Language英语
Funding OrganizationEngineering and Physical Sciences Research Council(EP/L000296/1) ; Biotechnology and Biological Sciences Research Council(H012508) ; Leverhulme Trust(RF-2011-378) ; European Community(PITN-GA 2011-290011) ; Wellcome Trust(095183/Z/10/Z)
WOS Research AreaNeurosciences & Neurology
WOS SubjectNeurosciences
WOS IDWOS:000408705100010
WOS HeadingsScience & Technology ; Life Sciences & Biomedicine
WOS KeywordPRIMARY VISUAL-CORTEX ; MEDIAL TEMPORAL-LOBE ; PREFRONTAL CORTEX ; DECISION-MAKING ; NEURAL SYSTEMS ; IMPLICIT ; SEQUENCE ; FMRI ; HIPPOCAMPAL ; TASK
Citation statistics
Cited Times:5[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.psych.ac.cn/handle/311026/21911
Collection中国科学院心理健康重点实验室
Corresponding AuthorKourtzi, Zoe
Affiliation1.Chinese Acad Sci, Inst Psychol, Key Lab Mental Hlth, Beijing 100101, Peoples R China
2.Univ Cambridge, Dept Psychol, Downing Site, Cambridge CB2 3EB, England
3.Xian Jiaotong Liverpool Univ, Dept Math Sci, Suzhou 215123, Peoples R China
4.Univ Birmingham, Sch Comp Sci, Birmingham B15 2TT, W Midlands, England
First Author AffilicationKey Laboratory of Mental Health, CAS
Recommended Citation
GB/T 7714
Wang, Rui,Shen, Yuan,Tino, Peter,et al. Learning Predictive Statistics: Strategies and Brain Mechanisms[J]. JOURNAL OF NEUROSCIENCE,2017,37(35):8412-8427.
APA Wang, Rui,Shen, Yuan,Tino, Peter,Welchman, Andrew E.,&Kourtzi, Zoe.(2017).Learning Predictive Statistics: Strategies and Brain Mechanisms.JOURNAL OF NEUROSCIENCE,37(35),8412-8427.
MLA Wang, Rui,et al."Learning Predictive Statistics: Strategies and Brain Mechanisms".JOURNAL OF NEUROSCIENCE 37.35(2017):8412-8427.
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