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Multimodal imaging of brain connectivity reveals predictors of individual decision strategy in statistical learning
Karlaftis, Vasilis M.1; Giorgio, Joseph1; Vertes, Petra E.2; Wang, Rui3; Shen, Yuan4; Tino, Peter5; Welchman, Andrew E.1; Kourtzi, Zoe1
First AuthorVasilis M. Karlaftis
2019-03-01
Source PublicationNATURE HUMAN BEHAVIOUR
Correspondent Emailaew69@cam.ac.uk ; zk240@cam.ac.uk
ISSN2397-3374
SubtypeArticle
Volume3Issue:3Pages:297-307
Contribution Rank3
Abstract

Successful human behaviour depends on the brain's ability to extract meaningful structure from information streams and make predictions about future events. Individuals can differ markedly in the decision strategies they use to learn the environment's statistics, yet we have little idea why. Here, we investigate whether the brain networks involved in learning temporal sequences without explicit reward differ depending on the decision strategy that individuals adopt. We demonstrate that individuals alter their decision strategy in response to changes in temporal statistics and engage dissociable circuits: extracting the exact sequence statistics relates to plasticity in motor corticostriatal circuits, while selecting the most probable outcomes relates to plasticity in visual, motivational and executive corticostriatal circuits. Combining graph metrics of functional and structural connectivity, we provide evidence that learning-dependent changes in these circuits predict individual decision strategy. Our findings propose brain plasticity mechanisms that mediate individual ability for interpreting the structure of variable environments.

DOI10.1038/s41562-018-0503-4
Indexed BySCI
Language英语
Funding ProjectMRC[MR/K020706/1] ; (European Community's) Seventh Framework Programme (FP7/2007-2013)[PITN-GA-2011-290011] ; (European Community's) Seventh Framework Programme (FP7/2007-2013)[PITN-GA-2012-316746] ; Wellcome Trust[205067/Z/16/Z] ; Alan Turing Institute[TU/B/000095] ; Biotechnology and Biological Sciences Research Council[BB/P021255/1] ; Engineering and Physical Sciences Research Council[EP/L000296/1] ; Wellcome Trust[095183/Z/10/Z] ; Leverhulme Trust[RF-2011-378] ; Biotechnology and Biological Sciences Research Council[H012508]
WOS Research AreaPsychology ; Science & Technology - Other Topics ; Neurosciences & Neurology
WOS SubjectPsychology, Biological ; Multidisciplinary Sciences ; Neurosciences ; Psychology, Experimental
WOS IDWOS:000460952000022
PublisherNATURE PUBLISHING GROUP
WOS KeywordFUNCTIONAL CONNECTIVITY ; PREFRONTAL CORTEX ; WORKING-MEMORY ; HUMAN STRIATUM ; NETWORK ; SYSTEM ; CHOICE
Citation statistics
Document Type期刊论文
Identifierhttp://ir.psych.ac.cn/handle/311026/28606
Collection中国科学院心理健康重点实验室
Corresponding AuthorWelchman, Andrew E.; Kourtzi, Zoe
Affiliation1.Univ Cambridge, Dept Psychol, Cambridge, England
2.Univ Cambridge, Dept Psychiat, Behav & Clin Neurosci Inst, Cambridge, England
3.Chinese Acad Sci, Inst Psychol, Key Lab Mental Hlth, Beijing, Peoples R China
4.Nottingham Trent Univ, Sch Sci & Technol, Nottingham, England
5.Univ Birmingham, Sch Comp Sci, Birmingham, W Midlands, England
Recommended Citation
GB/T 7714
Karlaftis, Vasilis M.,Giorgio, Joseph,Vertes, Petra E.,et al. Multimodal imaging of brain connectivity reveals predictors of individual decision strategy in statistical learning[J]. NATURE HUMAN BEHAVIOUR,2019,3(3):297-307.
APA Karlaftis, Vasilis M..,Giorgio, Joseph.,Vertes, Petra E..,Wang, Rui.,Shen, Yuan.,...&Kourtzi, Zoe.(2019).Multimodal imaging of brain connectivity reveals predictors of individual decision strategy in statistical learning.NATURE HUMAN BEHAVIOUR,3(3),297-307.
MLA Karlaftis, Vasilis M.,et al."Multimodal imaging of brain connectivity reveals predictors of individual decision strategy in statistical learning".NATURE HUMAN BEHAVIOUR 3.3(2019):297-307.
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