Bayesian modelling captures inter-individual differences in social belief computations in the putamen and insula

Area of Science:

• Neuroscience
• Cognitive Science
• Computational Psychiatry

Background:

• Understanding social cues is crucial for human interaction.
• Most research uses explicit social learning, but real-life integration is often spontaneous.
• Gaze cues are vital implicit signals for inferring intentions and guiding behavior.

Purpose of the Study:

• To investigate the neural mechanisms underlying spontaneous social cue integration during learning and decision-making.
• To examine how gaze direction influences probabilistic learning and choice behavior.
• To utilize computational modeling with fMRI to dissect the brain's response to implicit social information.

Main Methods:

• Acquired behavioral and functional magnetic resonance imaging (fMRI) data from 50 participants.
• Employed a probabilistic learning task with implicit social gaze cues from a computer-generated face.
• Inferred individual belief trajectories using a hierarchical Gaussian filter (HGF) for neural analysis.

Main Results:

• Social prediction errors during learning correlated with activity in the inferior frontal gyrus and insula.
• Beliefs about social cue accuracy during decision-making engaged the inferior temporal gyrus, putamen, and pallidum.
• The putamen and insula showed activity related to individual differences in weighting social cues.

Conclusions:

• Model-based fMRI provides insights into the neural basis of spontaneous social cue integration.
• Specific components of the basal ganglia are mechanistically involved in processing social information for learning and decision-making.
• This research elucidates the brain's natural ability to use subtle social signals for adaptive behavior.