A Multitude of Neural Representations Behind Multisensory "Social Norm" Processing

Multidimensional neural representations of social features during movie viewing

The social world is dynamic and contextually embedded. Yet, most studies utilize simple stimuli that do not capture the complexity of everyday social episodes. To address this, we implemented a movie viewing paradigm and investigated how everyday social episodes are processed in the brain. Participants watched one of two movies during an MRI scan. Neural patterns from brain regions involved in social perception, mentalization, action observation and sensory processing were extracted. Representational similarity analysis results revealed that several labeled social features (including social interaction, mentalization, the actions of others, characters talking about themselves, talking about others and talking about objects) were represented in the superior temporal gyrus (STG) and middle temporal gyrus (MTG). The mentalization feature was also represented throughout the theory of mind network, and characters talking about others engaged the temporoparietal junction (TPJ), suggesting that listeners may spontaneously infer the mental state of those being talked about. In contrast, we did not observe the action representations in the frontoparietal regions of the action observation network. The current findings indicate that STG and MTG serve as key regions for social processing, and that listening to characters talk about others elicits spontaneous mental state inference in TPJ during natural movie viewing.

Functional selectivity for social interaction perception in the human superior temporal sulcus during natural viewing

Recognizing others' social interactions is a crucial human ability. Using simple stimuli, previous studies have shown that social interactions are selectively processed in the superior temporal sulcus (STS), but prior work with movies has suggested that social interactions are processed in the medial prefrontal cortex (mPFC), part of the theory of mind network. It remains unknown to what extent social interaction selectivity is observed in real world stimuli when controlling for other covarying perceptual and social information, such as faces, voices, and theory of mind. The current study utilizes a functional magnetic resonance imaging (fMRI) movie paradigm and advanced machine learning methods to uncover the brain mechanisms uniquely underlying naturalistic social interaction perception. We analyzed two publicly available fMRI datasets, collected while both male and female human participants (n = 17 and 18) watched two different commercial movies in the MRI scanner. By performing voxel-wise encoding and variance partitioning analyses, we found that broad social-affective features predict neural responses in social brain regions, including the STS and mPFC. However, only the STS showed robust and unique selectivity specifically to social interactions, independent from other covarying features. This selectivity was observed across two separate fMRI datasets. These findings suggest that naturalistic social interaction perception recruits dedicated neural circuity in the STS, separate from the theory of mind network, and is a critical dimension of human social understanding.

A Guide to Representational Similarity Analysis for Social Neuroscience

Representational similarity analysis (RSA) is a computational technique that uses pairwise comparisons of stimuli to reveal their representation in higher-order space. In the context of neuroimaging, mass-univariate analyses and other multivariate analyses can provide information on what and where information is represented but have limitations in their ability to address how information is represented. Social neuroscience is a field that can particularly benefit from incorporating RSA techniques to explore hypotheses regarding the representation of multidimensional data, how representations can predict behavior, how representations differ between groups and how multimodal data can be compared to inform theories. The goal of this paper is to provide a practical as well as theoretical guide to implementing RSA in social neuroscience studies.

Neural Representations Behind 'Social Norm' Inferences In Humans

Humans are highly skilled in social reasoning, e.g., inferring thoughts of others. This mentalizing ability systematically recruits brain regions such as Temporo-Parietal Junction (TPJ), Precuneus (PC) and medial Prefrontal Cortex (mPFC). Further, posterior mPFC is associated with allocentric mentalizing and conflict monitoring while anterior mPFC is associated with self-reference (egocentric) processing. Here we extend this work to how we reason not just about what one person thinks but about the abstract shared social norm. We apply functional magnetic resonance imaging to investigate neural representations while participants judge the social congruency between emotional auditory utterances in relation to visual scenes according to how ‘most people’ would perceive it. Behaviorally, judging according to a social norm increased the similarity of response patterns among participants. Multivoxel pattern analysis revealed that social congruency information was not represented in visual and auditory areas, but was clear in most parts of the mentalizing network: TPJ, PC and posterior (but not anterior) mPFC. Furthermore, interindividual variability in anterior mPFC representations was inversely related to the behavioral ability to adjust to the social norm. Our results suggest that social norm inferencing is associated with a distributed and partially individually specific representation of social congruency in the mentalizing network.