Functional brain networks for learning predictive statistics
文献类型:期刊论文
作者 | Giorgio, Joseph1; Karlaftis, Vasilis M.1; Wang, Rui1,2; Shen, Yuan3,4; Tino, Peter4; Welchman, Andrew1; Kourtzi, Zoe1 |
刊名 | CORTEX |
出版日期 | 2018-10-01 |
卷号 | 107页码:204-219 |
ISSN号 | 0010-9452 |
关键词 | Brain Plasticity Fmri Functional Network Connectivity Individual Differences Statistical Learning |
DOI | 10.1016/j.cortex.2017.08.014 |
文献子类 | Article |
英文摘要 | Making predictions about future events relies on interpreting streams of information that may initially appear incomprehensible. This skill relies on extracting regular patterns in space and time by mere exposure to the environment (i.e., without explicit feedback). Yet, we know little about the functional brain networks that mediate this type of statistical learning. Here, we test whether changes in the processing and connectivity of functional brain networks due to training relate to our ability to learn temporal regularities. By combining behavioral training and functional brain connectivity analysis, we demonstrate that individuals adapt to the environment's statistics as they change over time from simple repetition to probabilistic combinations. Further, we show that individual learning of temporal structures relates to decision strategy. Our fMRI results demonstrate that learning-dependent changes in fMRI activation within and functional connectivity between brain networks relate to individual variability in strategy. In particular, extracting the exact sequence statistics (i.e., matching) relates to changes in brain networks known to be involved in memory and stimulus-response associations, while selecting the most probable outcomes in a given context (i.e., maximizing) relates to changes in frontal and striatal networks. Thus, our findings provide evidence that dissociable brain networks mediate individual ability in learning behaviorally-relevant statistics. (C) 2017 The Authors. Published by Elsevier Ltd. |
WOS关键词 | Medial Temporal-lobe ; Prefrontal Cortex ; Individual Variability ; Memory Retrieval ; Visual-attention ; Episodic Memory ; Neural Circuits ; Working-memory ; Basal Ganglia ; Implicit |
资助项目 | Biotechnology and Biological Sciences Research Council[H012508] ; Leverhulme Trust[RF-2011-378] ; European Community[PITN-GA-2012-316746] ; European Community[PITN-GA-2011-290011] ; Wellcome Trust[095183/Z/10/Z] ; Engineering and Physical Sciences Research Council[EP/L000296/1] |
WOS研究方向 | Behavioral Sciences ; Neurosciences & Neurology |
语种 | 英语 |
出版者 | ELSEVIER MASSON, CORPORATION OFFICE |
WOS记录号 | WOS:000448092300018 |
源URL | [http://ir.psych.ac.cn/handle/311026/27401] |
专题 | 心理研究所_中国科学院心理健康重点实验室 |
通讯作者 | Kourtzi, Zoe |
作者单位 | 1.Univ Cambridge, Dept Psychol, Cambridge, England 2.Chinese Acad Sci, Inst Psychol, Key Lab Mental Hlth, Beijing, Peoples R China 3.Xian Jiaotong Liverpool Univ, Dept Math Sci, Suzhou, Peoples R China 4.Univ Birmingham, Sch Comp Sci, Birmingham, W Midlands, England |
推荐引用方式 GB/T 7714 | Giorgio, Joseph,Karlaftis, Vasilis M.,Wang, Rui,et al. Functional brain networks for learning predictive statistics[J]. CORTEX,2018,107:204-219. |
APA | Giorgio, Joseph.,Karlaftis, Vasilis M..,Wang, Rui.,Shen, Yuan.,Tino, Peter.,...&Kourtzi, Zoe.(2018).Functional brain networks for learning predictive statistics.CORTEX,107,204-219. |
MLA | Giorgio, Joseph,et al."Functional brain networks for learning predictive statistics".CORTEX 107(2018):204-219. |
入库方式: OAI收割
来源:心理研究所
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