Humans are often involved in complex social relationships, where they exhibit biased behavior when they process information from neighbors (e.g., irrational DeGroot learning) and cognitive biases on perceiving social network structures (e.g., egocentric biases, network centrality, etc.). But little is known about the cognitive reason behind. Here we purpose a unified computational framework (reduced representation model, RRM) to deal with the problems, which assumes people represent an optimal reduced network based on the trade-off of utility and cognitive cost for the representation, and make rational inference on it, where DeGroot-like behavior emerges. We did simulations to show RRM can provide an underlying explanation for DeGroot model and human perceptual biases, and tested model predictions in previous dataset (n=209), lab experiment (n=248) and field data. Our work provides an optimal way to depict social network representation when considering human cognitive limitations, and may help understand widespread human biases in social environments.

Both basal ganglia (BG) and orbitofrontal cortex (OFC) have been widely implicated in social and non-social decision-making. However, unlike OFC damage, BG pathology is not typically associated with disturbances in social functioning. Here we studied the behavior of patients with focal lesions to either BG or OFC in a multi-strategy competitive game known to engage these regions. We find that whereas OFC patients are significantly impaired, BG patients show intact learning in the economic game. By contrast, when information about the strategic context is absent, both cohorts are significantly impaired. Computational modeling further shows a preserved ability in BG patients to learn by anticipating and responding to the behavior of others using the strategic context. These results suggest that apparently divergent findings on BG contribution to social decision-making may instead reflect a model where higher-order learning processes are dissociable from trial-and-error learning, and can be preserved despite BG damage.