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Connectome-based model predicts individual differences in propensity to trust.

Xiaping Lu1,2,3, Ting Li4, Zhichao Xia3

  • 1Center for Brain Disorders and Cognitive Sciences, Shenzhen Univeristy, Shenzhen, China.

Human Brain Mapping
|January 12, 2019
PubMed
Summary
This summary is machine-generated.

Resting-state functional connectivity (RSFC) can predict individual differences in trust propensity. Key brain regions integrate to form networks crucial for trust, offering a potential neuromarker for disorders.

Keywords:
connectome-based predictive modelingindividual differenceresting-state functional connectivitysocial decision makingtrust

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Area of Science:

  • Neuroscience
  • Social Psychology
  • Computational Psychiatry

Background:

  • Trust is fundamental to social interactions and relationships.
  • Understanding the neural basis of trust propensity is crucial.
  • Predicting trust using task-free neuroimaging remains challenging.

Purpose of the Study:

  • To predict individual variations in trust propensity using whole-brain resting-state functional connectivity (RSFC).
  • To identify specific brain networks and nodes associated with trust.
  • To explore the influence of social and risk preferences on trust and its neural correlates.

Main Methods:

  • Combined a one-shot trust game with connectome-based predictive modeling.
  • Utilized whole-brain resting-state functional connectivity (RSFC) data.
  • Analyzed associations between RSFC and behavioral measures of trust, altruism, social preferences, and risk preferences.

Main Results:

  • RSFC accurately predicted individual differences in trust propensity.
  • Key predictive nodes included the caudate, amygdala, lateral prefrontal cortex, temporal-parietal junction, and temporal pole.
  • Brain-behavior associations were specific to trust, not altruistic preferences, and modulated by social (horizontal collectivism) versus risk (impulsiveness) preferences.

Conclusions:

  • Whole-brain RSFC can predict propensity to trust.
  • The findings highlight the role of integrated large-scale brain networks in trust.
  • This approach offers a potential objective neuromarker for trust impairments in mental disorders.