Normativity vs. uniqueness: effects of social relationship strength on neural representations of others.

Understanding others involves inferring traits and intentions, a process complicated by our reliance on stereotypes and generalized information when we lack personal information. Yet, as relationships are formed, we shift toward nuanced and individualized perceptions of others. This study addresses how relationship strength influences the creation of unique or normative representations of others in key regions known to be involved in social cognition. Employing a round-robin interpersonal perception paradigm (N = 111, 20 groups of five to six people), we used functional magnetic resonance imaging to examine whether the strength of social relationships modulated the degree to which multivoxel patterns of activity that represented a specific other were similar to a normative average of all others in the study. Behaviorally, stronger social relationships were associated with more normative trait endorsements. Neural findings reveal that closer relationships lead to more unique representations in the medial prefrontal cortex and anterior insula, areas associated with mentalizing and person perception. Conversely, more generalized representations emerge in posterior regions like the posterior cingulate cortex, indicating a complex interplay between individuated and generalized processing of social information in the brain. These findings suggest that cortical regions typically associated with social cognition may compute different kinds of information when representing the distinctiveness of others.

Social Relationship Strength Modulates the Similarity of Brain-to-Brain Representations of Group Members.

Within our societies, humans form co-operative groups with diverse levels of relationship quality among individual group members. In establishing relationships with others, we use attitudes and beliefs about group members and the group as a whole to establish relationships with particular members of our social networks. However, we have yet to understand how brain responses to group members facilitate relationship quality between pairs of individuals. We address this here using a round-robin interpersonal perception paradigm in which each participant was both a perceiver and target for every other member of their group in a set of 20 unique groups of between 5 and 6 members in each (total N = 111). Using functional magnetic resonance imaging, we show that measures of social relationship strength modulate the brain-to-brain multivoxel similarity patterns between pairs of participants' responses when perceiving other members of their group in regions of the brain implicated in social cognition. These results provide evidence for a brain mechanism of social cognitive processes serving interpersonal relationship strength among group members.

Generalizing effects of frontostriatal structural connectivity on self-esteem using predictive modeling.

Determining the generalizability of biological mechanisms supporting psychological constructs is a central goal of cognitive neuroscience. Self-esteem is a popular psychological construct that is associated with a variety of measures of mental health and life satisfaction. Recently, there has been interest in identifying biological mechanisms that support individual differences in self-esteem. Understanding the biological basis of self-esteem requires identifying predictive biomarkers of self-esteem that generalize across groups of individuals. Previous research using diffusion magnetic resonance imaging has shown that self-esteem is related to the integrity of structural connections linking frontostriatal brain systems involved in self-referential processing and reward. However, these findings were based on a small, relatively homogeneous group of participants. In the current study, we used an out-of-sample predictive modeling approach to generalize the results of the previous study to an independent sample of participants more than twice the size of the original study. We found that both linear univariate and multivariate machine learning models trained on frontostriatal integrity from the original data significantly predicted self-esteem in the independent dataset. These findings underscore the relationship between self-esteem and frontostriatal connectivity and suggest these results are robust to differences in scanning acquisition, analytic methods, and participant demographics.