The neural representational geometry of social perception

Abstract

An emerging focus on the geometry of representational structures is advancing a variety of areas in social perception, including social categorization, emotion perception, and trait impressions. Here, we review recent studies adopting a representational geometry approach, and argue that important advances in social perception can be gained by triangulating on the structure of representations via three levels of analysis: neuroimaging, behavioral measures, and computational modeling. Among other uses, this approach permits broad and comprehensive tests of how bottom-up facial features and visual processes as well as top-down social cognitive factors and conceptual processes shape perceptions of social categories, emotion, and personality traits. Although such work is only in its infancy, a focus on corroborating representational geometry across modalities is allowing researchers to use multiple levels of analysis to constrain theoretical models in social perception. This approach holds promise to further our understanding of the multiply determined nature of social perception and its neural basis.

A Guide To Representational Similarity Analysis for Social Neuroscience

“…For behavioral RDMs, the ratings or measures between pairs of stimuli are compared to create an RDM. Comparisons between two different behavioral ratings in a task, for instance, valence or arousal, can be calculated using measures of distance, such as Euclidean distance (Freeman et al, 2018;Kragel and LaBar, 2016). The RDM is created in the same manner as a neural DMN, resulting in a matrix that is also symmetrical about its diagonal and has the same number of rows and columns, as the same stimuli must be used in both tasks ( Figure 2B).…”

“…RSA has been used to test hypotheses about the neural representation of social categories and dimensions (Chavez and Heatherton, 2014;Freeman et al, 2018;Pegado et al, 2018;Vida et al, 2017;Wasserman et al, 2017). In most of these studies, the stimuli that are compared can be dimensionalized along some predefined metric.…”

“…In vision research, stimulus dimensions such as hue, luminance and line orientation can be parametrically manipulated and the representational sensitivity of visual cortex measured. In social neuroscience, many stimuli can also be Freeman et al, 2018;Stolier and Freeman, 2016;Stolier et al, 2018b), actions can vary on kinematics, effectors, transitivity and intentions (Urgen et al, 2019;Wurm et al, 2017), social concepts can vary on affective and psycholinguistic dimensions (Thornton and Tamir, 2017) and friendships can vary in their social distance and network topology (Parkinson et al, 2014;Parkinson et al, 2017). With this new tool, researchers can even investigate complex representations such as morality (Pegado et al, 2018a;Pegado et al, 2018b;van Baar et al, 2019;Volz et al, 2017;Wasserman et al, 2017) and the development of object concepts (Long et al, 2018).…”

Editorial overview: New advances in social neuroscience: from neural computations to social structures

“…Multivoxel pattern classification enriches our understanding by allowing us to explore the dimensionality of the representational space of our brain (Freeman, Stolier, Brooks, & Stillerman, 2018;Weaverdyck & Parkinson, 2018): what processes are more alike, which are more different? Are felt and perceived emotions represented in a similar code (e.g., Zaki, Ager, Singer, Keysers, & Gazzola, 2016)?…”

“…And to what extend does a neural structure support multiple representations or processes (e.g., Gilbert, Swencionis, & Amodio, 2012)? This trend toward assessing the roles of distributed patterns of activity, either within a region or across multiple regions, has produced new theoretical models of how we perceive people, form impressions, and update impressions (Freeman et al, 2018;Hackel & Amodio, 2018;Mende-Seidlecki, 2018).…”