Prosocial decision-making under cognitive constraints: A resting-state functional magnetic resonance imaging study based on relevance vector regression analysis model

This study aims to reveal the role of individual differences at the neural level through resting state functional magnetic resonance imaging technology. This study calculates the behavioral indicators of cognitive limitations regulating pro social decision-making based on two ways of manipulating cognitive limitations (time pressure and cognitive load), and predicts this indicator through resting state functional magnetic resonance imaging and correlation vector regression to establish a functional connectivity network.

The results showed that a brain network composed of negative emotions (insula, amygdala), empathy (temporal parietal joint area, medial cingulate gyrus), social cognition (temporal parietal joint area), and subjective value assessment (ventral striatum, ventral medial prefrontal cortex) related brain regions can effectively predict this indicator. The functional connections in the bilateral temporoparietal joint area of subjects with high emotional empathy traits were significantly higher than those of subjects with low emotional empathy traits, and this functional connection was significantly positively correlated with emotional empathy traits.