Prediction of trust propensity from intrinsic brain morphology and functional connectome

被引:32
作者
Feng, Chunliang [1 ,2 ,3 ]
Zhu, Zhiyuan [4 ,5 ]
Cui, Zaixu [6 ]
Ushakov, Vadim [7 ,8 ]
Dreher, Jean-Claude [9 ]
Luo, Wenbo [10 ]
Gu, Ruolei [11 ,12 ]
Wu, Xia [4 ,5 ]
Krueger, Frank [13 ,14 ]
机构
[1] South China Normal Univ, Minist Educ, Key Lab Brain Cognit & Educ Sci, Guangzhou, Peoples R China
[2] South China Normal Univ, Ctr Studies Psychol Applicat, Sch Psychol, Guangzhou, Peoples R China
[3] South China Normal Univ, Guangdong Key Lab Mental Hlth & Cognit Sci, Guangzhou, Peoples R China
[4] Beijing Normal Univ, Sch Artificial Intelligence, Beijing, Peoples R China
[5] Beijing Normal Univ, Minist Educ, Engn Res Ctr Intelligent Technol & Educ Applicat, Beijing, Peoples R China
[6] Univ Penn, Dept Psychiat, Perelman Sch Med, Philadelphia, PA 19104 USA
[7] Kurchatov Inst, Natl Res Ctr, Moscow, Russia
[8] Natl Res Nucl Univ MEPhI, Moscow Engn Phys Inst, Moscow, Russia
[9] CNRS, Inst Sci Cognit Marc Jeannerod, Neuroecon Reward & Decis Making Lab, Bron, France
[10] Liaoning Normal Univ, Res Ctr Brain & Cognit Neurosci, Dalian, Peoples R China
[11] Chinese Acad Sci, Inst Psychol, Key Lab Behav Sci, Beijing, Peoples R China
[12] Univ Chinese Acad Sci, Dept Psychol, Beijing, Peoples R China
[13] George Mason Univ, Sch Syst Biol, Fairfax, VA 22030 USA
[14] George Mason Univ, Dept Psychol, Fairfax, VA 22030 USA
基金
中国国家自然科学基金; 俄罗斯科学基金会;
关键词
functional decoding; gray matter; individualized prediction; large-scale brain networks; trust propensity; MEDIAL PREFRONTAL CORTEX; FINGER COUNTING HABITS; EMOTION REGULATION; LINEAR-MODELS; CONNECTIVITY; NETWORK; RECIPROCITY; THICKNESS; BEHAVIOR; NUMBERS;
D O I
10.1002/hbm.25215
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Trust forms the basis of virtually all interpersonal relationships. Although significant individual differences characterize trust, the driving neuropsychological signatures behind its heterogeneity remain obscure. Here, we applied a prediction framework in two independent samples of healthy participants to examine the relationship between trust propensity and multimodal brain measures. Our multivariate prediction analyses revealed that trust propensity was predicted by gray matter volume and node strength across multiple regions. The gray matter volume of identified regions further enabled the classification of individuals from an independent sample with the propensity to trust or distrust. Our modular and functional decoding analyses showed that the contributing regions were part of three large-scale networks implicated in calculus-based trust strategy, cost-benefit calculation, and trustworthiness inference. These findings do not only deepen our neuropsychological understanding of individual differences in trust propensity, but also provide potential biomarkers in predicting trust impairment in neuropsychiatric disorders.
引用
收藏
页码:175 / 191
页数:17
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