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2017 Fiscal Year Final Research Report

Learning algorithm and neural basis of reducing market anomalies

Research Project

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Project/Area Number 15H03124
Research Category

Grant-in-Aid for Scientific Research (B)

Allocation TypeSingle-year Grants
Section一般
Research Field Basic / Social brain science
Research InstitutionTamagawa University

Principal Investigator

MATSUMOTO Kenji  玉川大学, 脳科学研究所, 教授 (50300900)

Co-Investigator(Renkei-kenkyūsha) KOIKE Yasuharu  東京工業大学, 科学技術創成研究院, 教授 (10302978)
Research Collaborator MATSUMORI Kaosu  
YOMOGIDA Yukihito  
IIJIMA Kazuki  
AOKI Ryuta  
IZUMA Keise  
SUZUKI Shinsuke  
MURAYAMA Kou  
SAKAKI Michiko  
FOO Jerome  
SUGIURA Ayaka  
Project Period (FY) 2015-04-01 – 2018-03-31
Keywordsニューロエコノミクス / 認知バイアス / 学習アルゴリズム / 脳
Outline of Final Research Achievements

We proposed an exponentially biased Bayesian update model with its underlying neural circuits, which can explain most cognitive biases in human probability judgments as well as electrophysiological findings on experimental animals. The model also provides a unified account for some psychiatric diseases. We applied the model to determine the learning algorism to diminish the cognitive bias in an experimentally designed market. In addition, we proposed a new behavior change theory that is consistent to the findings in behavioral economics.

Free Research Field

認知神経科学

URL: 

Published: 2019-03-29  

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