Paper Abstract and Keywords |
Presentation |
2018-01-27 09:55
Neural Representations of Value Formation by Long-Term Learning Masaki Yonekawa (NAIST/ATR), Saori Tanaka (ATR) NC2017-58 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
It is said that there are 2 types of human’s behavior, one is a stable behavior, the other is flexible behavior. According to previous studies, these behaviors are implemented in different regions of striatum which is the component of basal ganglia. However, previous studies have some problems that the task to investigate stable and flexible behavior is different between animal and human. For example, the study whose subjects are monkeys use a long-term value learning task which takes several months or years to make subjects acquire stable behavior. On the other hand, most research in humans use a short-term value learning task. Here, we identified regions involved in stable and flexible behavior by using functional magnetic resonance imaging (fMRI)fMRI during long-term value learning task. In addition to this, we conducted a task that subjects have to change value they learned in order to elucidate regions involved in flexible behavior. As a result, we found that posterior striatum is related to acquisition of stable behavior, the stronger stable behavior the richer information of anterior striatum and the stronger flexible behavior the richer information of posterior striatum. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
fMRI / value formation / striatum / long-term learning / machine learning / / / |
Reference Info. |
IEICE Tech. Rep., vol. 117, no. 417, NC2017-58, pp. 47-52, Jan. 2018. |
Paper # |
NC2017-58 |
Date of Issue |
2018-01-19 (NC) |
ISSN |
Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
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NC2017-58 |
Conference Information |
Committee |
MBE NC NLP |
Conference Date |
2018-01-26 - 2018-01-27 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Kyushu Institute of Technology |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
ME, generalImplementation of Neuro Computing,Analysis and Modeling of Human Science, |
Paper Information |
Registration To |
NC |
Conference Code |
2018-01-MBE-NC-NLP |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
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(See Japanese page) |
Title (in English) |
Neural Representations of Value Formation by Long-Term Learning |
Sub Title (in English) |
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fMRI |
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value formation |
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striatum |
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long-term learning |
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machine learning |
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1st Author's Name |
Masaki Yonekawa |
1st Author's Affiliation |
Nara Institute of Science and Technology/Advanced Telecommunications Research Institute International (NAIST/ATR) |
2nd Author's Name |
Saori Tanaka |
2nd Author's Affiliation |
Advanced Telecommunications Research Institute International (ATR) |
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Speaker |
Author-1 |
Date Time |
2018-01-27 09:55:00 |
Presentation Time |
25 minutes |
Registration for |
NC |
Paper # |
NC2017-58 |
Volume (vol) |
vol.117 |
Number (no) |
no.417 |
Page |
pp.47-52 |
#Pages |
6 |
Date of Issue |
2018-01-19 (NC) |
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