Developments of Methods for Information Decoding and Manipulation from Subcortical Prosocial System

2018 Fiscal Year Final Research Report

• Project/Area Number: 26242087
• Research Category: Grant-in-Aid for Scientific Research (A)
• Allocation Type: Single-year Grants
• Section: 一般
• Research Field: Basic / Social brain science
• Research Institution: National Institute of Information and Communications Technology
• Principal Investigator: Haruno Masahiko 国立研究開発法人情報通信研究機構, 脳情報通信融合研究センター脳情報工学研究室, 研究マネージャー (40395124)
• Co-Investigator(Kenkyū-buntansha): 二本杉 剛 大阪経済大学, 経済学部, 准教授 (10616791) ; 田村 弘 大阪大学, 生命機能研究科, 准教授 (80304038)
• Research Collaborator: Tanaka Toshiko
• Project Period (FY): 2014-04-01 – 2019-03-31
• Keywords: 脳情報 / 扁桃体 / デコーディング / 社会行動

Outline of Final Research Achievements

In this study, we aimed to develop a method to predict various characteristics of subjects by extracting amygdala activity patterns common to the subjects. As a result of the fMRI experiment in this study, the activity of the prefrontal area, which is the center of higher cognitive function of the cerebral cortex, expresses "guilt" and the activity of the amygdala, which is a subcortical area, "inequity". We also conducted tDCS experiment on the prefrontal area and found that guilt aversion but not inequity aversion increased.
In addition, we obtained new results indicating that the amygdala activity pattern in correlation with "inequity" predicts current and future (one- year later) depression tendency.

Free Research Field

計算論的社会脳科学

Academic Significance and Societal Importance of the Research Achievements

本研究では、皮質下の領域の脳活動から社会行動に関する情報を解読する手法を計算論的神経科学と行動経済学の分野間協力で開発した。この手法は扁桃体で行われる情報処理を明らかにするのみでなく、これまで機能解析が難しかったヒトの皮質下微細構造の情報処理に大きく貢献し、新たな神経疾患基盤の発見や高精度な精神疾患、パーソナリティ同定・予測手法の開発につながることが期待される。