Presentation 2007-03-15
Functional dissociation of hidden state estimation and dynamics identification in prefrontal cortex
Satoshi MORIMOTO, Wako YOSHIDA, Shin ISHII,
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Abstract(in English) Decision making in a dynamic environment rests critically on the identification of the environmental dynamics. When the environment is partially observable, it is neccessary to estimate the hidden state using the uncertain observation is needed. Despite considerable interests in the estimation function of the prefrontal cortex, the functional dissociation between the hidden state estimation and dynamics identification has not been studied yet. In this study, we designed a decision making task in which the subjects were required to estimate both the hidden state and the dynamics model using the uncertain information, as an extention of 'Tiger problem' a typical partially observable problem. Our fMRI results showed that the activation of the left anterior prefrontal cortex and the right lateral prefrontal were correlated with the uncertainty of state and dynamics estimation, respectively.
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Keyword(in English) hidden state estimation / dynamics identification / anterior prefrontal cortex / dorsolateral prefrontal cortex / fMRI
Paper # NC2006-167
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Committee NC
Conference Date 2007/3/8(1days)
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Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Functional dissociation of hidden state estimation and dynamics identification in prefrontal cortex
Sub Title (in English)
Keyword(1) hidden state estimation
Keyword(2) dynamics identification
Keyword(3) anterior prefrontal cortex
Keyword(4) dorsolateral prefrontal cortex
Keyword(5) fMRI
1st Author's Name Satoshi MORIMOTO
1st Author's Affiliation Nara Institute of Science and Technology()
2nd Author's Name Wako YOSHIDA
2nd Author's Affiliation Nara Institute of Science and Technology
3rd Author's Name Shin ISHII
3rd Author's Affiliation Nara Institute of Science and Technology
Date 2007-03-15
Paper # NC2006-167
Volume (vol) vol.106
Number (no) 589
Page pp.pp.-
#Pages 6
Date of Issue