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Critical evidence for the prediction error theory in associative learning

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Title: Critical evidence for the prediction error theory in associative learning
Authors: Terao, Kanta Browse this author
Matsumoto, Yukihisa Browse this author →KAKEN DB
Mizunami, Makoto Browse this author →KAKEN DB
Keywords: Classical conditioning
Cognitive neuroscience
Issue Date: 10-Mar-2015
Publisher: NATURE PUBLISHING GROUP
Journal Title: Scientific Reports
Volume: 5
Start Page: 8929
Publisher DOI: 10.1038/srep08929
Abstract: In associative learning in mammals, it is widely accepted that the discrepancy, or error, between actual and predicted reward determines whether learning occurs. Complete evidence for the prediction error theory, however, has not been obtained in any learning systems: Prediction error theory stems from the finding of a blocking phenomenon, but blocking can also be accounted for by other theories, such as the attentional theory. We demonstrated blocking in classical conditioning in crickets and obtained evidence to reject the attentional theory. To obtain further evidence supporting the prediction error theory and rejecting alternative theories, we constructed a neural model to match the prediction error theory, by modifying our previous model of learning in crickets, and we tested a prediction from the model: the model predicts that pharmacological intervention of octopaminergic transmission during appetitive conditioning impairs learning but not formation of reward prediction itself, and it thus predicts no learning in subsequent training. We observed such an "auto-blocking", which could be accounted for by the prediction error theory but not by other competitive theories to account for blocking. This study unambiguously demonstrates validity of the prediction error theory in associative learning.
Rights: http://creativecommons.org/licenses/by/4.0/
Type: article
URI: http://hdl.handle.net/2115/58562
Appears in Collections:理学院・理学研究院 (Graduate School of Science / Faculty of Science) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)

Submitter: 水波 誠

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