Connectome‐based model predicts individual differences in propensity to trust. Issue 6 (11th January 2019)

• Record Type: Journal Article
• Authors: Lu, Xiaping; Li, Ting; Xia, Zhichao; Zhu, Ruida; Wang, Li; Luo, Yue‐Jia; Feng, Chunliang; Krueger, Frank
• Is Part Of: Human brain mapping. Volume 40:Issue 6(2019)
• Page Start: 1942
• Page End: 1954
• Publication Date: 2019-01-11
• Subjects: connectome‐based predictive modeling -- individual difference -- resting‐state functional connectivity -- social decision making -- trust; Brain mapping -- Periodicals; 611.81
• DOI: 10.1002/hbm.24503
• Languages: English
• ISSNs: 1065-9471

Abstract

Abstract: Trust constitutes a fundamental basis of human society and plays a pivotal role in almost every aspect of human relationships. Although enormous interest exists in determining the neuropsychological underpinnings of a person's propensity to trust utilizing task‐based fMRI; however, little progress has been made in predicting its variations by task‐free fMRI based on whole‐brain resting‐state functional connectivity (RSFC). Here, we combined a one‐shot trust game with a connectome‐based predictive modeling approach to predict propensity to trust from whole‐brain RSFC. We demonstrated that individual variations in the propensity to trust were primarily predicted by RSFC rooted in the functional integration of distributed key nodes—caudate, amygdala, lateral prefrontal cortex, temporal–parietal junction, and the temporal pole—which are part of domain‐general large‐scale networks essential for the motivational, affective, and cognitive aspects of trust. We showed, further, that the identified brain‐behavior associations were only evident for trust but not altruistic preferences and that propensity to trust (and its underlying neural underpinnings) were modulated according to the extent to which a person emphasizes general social preferences (i.e., horizontal collectivism) rather than general risk preferences (i.e., trait impulsiveness). In conclusion, the employed data‐driven approach enables to predict propensity to trust from RSFC and highlights its potential use as an objective neuromarker of trust impairment in mental disorders.