Neural Mechanisms of Social Attribution from Faces

PROJECT SUMMARY Psychological studies have shown that social judgments from faces are ubiquitous, automatic, very rapid, and play critical roles in human social behavior, in both health and disease. The proposed project seeks to understand the neural mechanisms responsible. The goal of our study is to go beyond merely identifying the brain regions where social attributes of faces are represented, and to discover the mechanisms whereby we go from perceptual representations to social knowledge. To achieve this goal, we leverage the high temporal resolution of our recordings, the broad coverage of relevant brain areas that will be sampled, and the innovative analysis tools we have developed. The strengths of our data- driven approach will be as follows: (i) Predictive modeling with variance partitioning as a function of time will reveal what aspect of social judgments is attributable to visual features (shared variance). We will identify the specific set of visual features that are predictive and establish a mapping between these visual features and social representations as a function of time for each brain area, thereby providing fine-grained data on how social attribution representations emerge at specific points in time and in specific brain regions. This approach is designed to elucidate the mechanisms that bind perceptual face information with social knowledge. (ii) Contextual and electrical stimulation manipulations will experimentally perturb the relationship between visual features and social representations. Geometric analysis of the structure of the population code allows us to assess how specific social judgments are suppressed or amplified, thereby establishing a mechanism for how context changes the mapping between faces and the social attributions we established as part of (i). (iii) Decoding analysis will assess what aspect of the visual-social mapping is predictive of behavior in a given trial, thereby identifying a mapping between internal representations of social attributions and the actual choices patients make in a given trial. (iv) Inter-areal interaction analysis and latency comparisons will establish when information about a given social attribution is first available and how this information spreads to other anatomical nodes. Simultaneous recordings from multiple brain areas present a rare and unique opportunity to assess the role of directional interactions. We will use complementary measures of inter-areal spike-field coherence, Granger causality analysis, phase coupling, lagged correlation (during rest and experimental conditions), and dynamic resting-state iEEG connectivity as well as the measure of repeated single-pulse stimulations (also known as cortico-cortical evoked potentials). Our project will provide a new and dynamic picture of the brain where populations of individual cells in a distributed network interact together in time and space to enable the human brain to extract socially relevant information from faces