Brain coding of social network structure

Abstract

To successfully navigate our social world, we keep track of other individuals' relations to ourselves and to each other. But how does the brain encode this information? To answer this question, we mined participants' social media (Facebook TM ) profiles to objectively characterize the relations between individuals in their real-life social networks. Under fMRI, participants answered questions on each of these individuals. Using representational similarity analysis, we identified social network structure coding in the defaultmode network (medial prefrontal, medial parietal and lateral parietal cortices). When regressing out subjective factors (ratings of personal affiliation, appearance and personality), social network structure information was uniquely found in the retrosplenial complex, a region implicated in spatial processing. In contrast, information on individuals' personality traits and affiliation to the subjects was found in the medial prefrontal and parietal cortices, respectively. These findings demonstrate a cortical division between representation of structural, trait-based and self-referenced social knowledge.

Bipartite functional fractionation within the neural system for social cognition supports the psychological continuity of selfvs.other

“…The representational structure of self-vs. other-concept. Our findings add to the literature that deciphering self-/other-referential thoughts is possible based on the patterns of DN and SN regions (Hassabis et al 2013;Thornton and Mitchell 2017;Courtney and Meyer 2020;Peer et al 2021). Moreover, our cross-classification analyses have important implications for the cognitive theories of self-processing.…”

“…Our findings add to the literature that deciphering self-/other-referential thoughts is possible based on the patterns of DN and SN regions (Hassabis et al . 2013; Thornton and Mitchell 2017; Courtney and Meyer 2020; Peer et al . 2021).…”

Language, Social, and Face Regions Are Affected in Toddlers with Autism and Predictive of Language Outcome

“…In this study, we surveyed the volume, thickness, and surface area of all regions across the brain to observe which size measures were reproducibly altered in ASD toddlers compared to TD toddlers. Identi ed brain regions are mainly involved in receptive and expressive language, social and face processing (bank STS, middle temporal, superior temporal, medial orbitofrontal, caudal anterior cingulate, posterior cingulate, pars opercularis, caudal middle frontal) 36,37,38,39,40,41,42,43,44,45,46 . Additional regions included those involved in motor, behavioral, cognitive, and language control; primary visual processing and interhemispheric communication (cerebellum; primary visual cortex, corpus callosum) 47, 48, 49, 50, 51, 52, 53, 54 .…”

Neural activation patterns evoked by social inference in the laboratory predict the number of real-life social contacts

“…Predictions of indices of social behavior unrelated to metrics of social network size point to the intriguing possibility that social inference activation in the pSTS reflects a latent variable that predicts individual differences in social functioning quite broadly (such as AQ and SRS-2 scores, ADOS SA severity scores, and the number of social contacts). It remains an open question how far this generalizability would extend, e.g., to more sophisticated metrics of social networks such as social network position, characteristics of social ties or social distance 22,65,66 , or even other social behaviors known to activate similar brain regions of the pSTS such as altruistic behavior 54,55 (see Figure S4B for illustration of overlap). Multi-trait-multi-method approaches (MTMM) 67 might be well suited to address these future questions, shedding further light on the underlying latent variable that we propose and on how the cognitive processes engaged could be causally related to social connectedness and everyday social functioning.…”