Relating brain structure images to personality characteristics using 3D convolution neural network

被引：3

作者：

Cao, Lixian ^{[1
]}

Liang, Yanchun ^{[1
,2
]}

Lv, Wei ^{[1
]}

Park, Kaechang ^{[3
]}

Miura, Yasuhiro ^{[3
]}

Shinomiya, Yuki ^{[3
]}

Yoshida, Shinichi ^{[3
]}

机构：

[1] Jilin Univ, Zhuhai Lab Key Lab Symbol Computat & Knowledge En, Minist Educ, Zhuhai Coll, Zhuhai 519041, Peoples R China

[2] Jilin Univ, Key Lab Symbol Computat & Knowledge Engn, Minist Educ, Coll Comp Sci & Technol, Changchun, Peoples R China

[3] Kochi Univ Technol, Sch Informat & Res Inst, Kochi 7828502, Japan

来源：

CAAI TRANSACTIONS ON INTELLIGENCE TECHNOLOGY | 2021年 / 6卷 / 03期

基金：

中国国家自然科学基金; 日本学术振兴会;

关键词：

All Open Access; Gold;

D O I：

10.1049/cit2.12021

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The Keras deep learning framework is employed to study MRI brain data in a preliminary analysis of brain structure using a convolutional neural network. The results obtained are matched with the content of personality questionnaires. The Big Five personality traits provide easy differentiation for dividing personalities into different groups. Until now, the highest accuracy obtained from the results of personality prediction from the analysis of brain structure is about 70%. Although there is still no effective evidence to prove a clear relationship between brain structure and personality, the obtained results could prove helpful in understanding the basic relationship between brain structure and personality characteristics.

引用

页码：338 / 346

页数：9

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