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Learning predictive statistics from temporal sequences: Dynamics and strategies
Wang, Rui1,2; Shen, Yuan3,4; Tino, Peter4; Welchman, Andrew E.2; Kourtzi, Zoe2
2017-10-01
发表期刊JOURNAL OF VISION
ISSN1534-7362
文章类型Article
卷号17期号:12页码:1-16
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摘要

Human behavior is guided by our expectations about the future. Often, we make predictions by monitoring how event sequences unfold, even though such sequences may appear incomprehensible. Event structures in the natural environment typically vary in complexity, from simple repetition to complex probabilistic combinations. How do we learn these structures? Here we investigate the dynamics of structure learning by tracking human responses to temporal sequences that change in structure unbeknownst to the participants. Participants were asked to predict the upcoming item following a probabilistic sequence of symbols. Using a Markov process, we created a family of sequences, from simple frequency statistics (e.g., some symbols are more probable than others) to context-based statistics (e.g., symbol probability is contingent on preceding symbols). We demonstrate the dynamics with which individuals adapt to changes in the environment's statistics-that is, they extract the behaviorally relevant structures to make predictions about upcoming events. Further, we show that this structure learning relates to individual decision strategy; faster learning of complex structures relates to selection of the most probable outcome in a given context (maximizing) rather than matching of the exact sequence statistics. Our findings provide evidence for alternate routes to learning of behaviorally relevant statistics that facilitate our ability to predict future events in variable environments.

关键词learning behavior vision
DOI10.1167/17.12.1
收录类别SCI ; SSCI
语种英语
项目资助者Engineering and Physical Sciences Research Council(EP/L000296/1) ; Biotechnology and Biological Sciences Research Council(H012508) ; Leverhulme Trust(RF-2011-378) ; European Community's Seventh Framework Programme (FP7)(PITN-GA-2011-290011) ; Wellcome Trust(095183/Z/10/Z)
WOS研究方向Ophthalmology
WOS类目Ophthalmology
WOS记录号WOS:000417128900001
WOS标题词Science & Technology ; Life Sciences & Biomedicine
关键词[WOS]8-MONTH-OLD INFANTS ; VISUAL-ATTENTION ; TIME ; PROBABILITIES ; PERFORMANCE ; LANGUAGE ; MEMORY ; MODEL ; TASK
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文献类型期刊论文
条目标识符http://ir.psych.ac.cn/handle/311026/26010
专题中国科学院心理健康重点实验室
作者单位1.Chinese Acad Sci, Key Lab Mental Hlth, Inst Psychol, Beijing, Peoples R China
2.Univ Cambridge, Dept Psychol, Cambridge, England
3.Xian Jiaotong Liverpool Univ, Dept Math Sci, Suzhou, Peoples R China
4.Univ Birmingham, Sch Comp Sci, Birmingham, W Midlands, England
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Wang, Rui,Shen, Yuan,Tino, Peter,et al. Learning predictive statistics from temporal sequences: Dynamics and strategies[J]. JOURNAL OF VISION,2017,17(12):1-16.
APA Wang, Rui,Shen, Yuan,Tino, Peter,Welchman, Andrew E.,&Kourtzi, Zoe.(2017).Learning predictive statistics from temporal sequences: Dynamics and strategies.JOURNAL OF VISION,17(12),1-16.
MLA Wang, Rui,et al."Learning predictive statistics from temporal sequences: Dynamics and strategies".JOURNAL OF VISION 17.12(2017):1-16.
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