Presentation 2003/6/19
Prediction of Striatum Neuronal Activities based on Reinforcement Learning Model
Kazuyuki SAMEJIMA, Kenji DOYA, Yasumasa UEDA, Minoru KIMURA,
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Abstract(in English) Recently, reinforcement learning as a computational model of the basal ganglia have been proposed. One of the earliest models is Barto's Actor-Critic model [4], which explain that the striatal neuronal activities represent reward expectation and a selected action. Doya [5] also proposed another model in which the striatum represents state-value function and action-value function. The action value function is the reward expectation for an action that is going to be selected. The main question of this study is whether the striatum neuronal activity is represent a selected action or an action-value function for particular action. To answer this question, we proposed a reinforcement learning task for the physiological experiment. In order to illustrate the experimental paradigm, we construct a computational model of striatum by a reinforcement learning model, and predict its behavior and neuronal activities.
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Keyword(in English) reinforcemente learning / basal ganglia / striatum activity / action value function / extra celluar recording
Paper # NC2003-9
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Committee NC
Conference Date 2003/6/19(1days)
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Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
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Title (in English) Prediction of Striatum Neuronal Activities based on Reinforcement Learning Model
Sub Title (in English)
Keyword(1) reinforcemente learning
Keyword(2) basal ganglia
Keyword(3) striatum activity
Keyword(4) action value function
Keyword(5) extra celluar recording
1st Author's Name Kazuyuki SAMEJIMA
1st Author's Affiliation ATR Computational Neuroscience laboratories:'Creating the brain', CREST JST()
2nd Author's Name Kenji DOYA
2nd Author's Affiliation ATR Computational Neuroscience laboratories
3rd Author's Name Yasumasa UEDA
3rd Author's Affiliation Department of phisiology, Kyoto prefecture university of medicine
4th Author's Name Minoru KIMURA
4th Author's Affiliation Department of phisiology, Kyoto prefecture university of medicine
Date 2003/6/19
Paper # NC2003-9
Volume (vol) vol.103
Number (no) 152
Page pp.pp.-
#Pages 6
Date of Issue