Avniel Singh Ghuman, PhD

Social perception unfolds in the real world, as we actively interact with people around us.Dr. Ghuman investigated the neural basis of real-world face perception using multi-electrode intracranial recordings during unscripted natural interactions with friends, family, and others. Computational models reconstructed videos of faces participants viewed from brain activity alone and highlighted a critical role for the social-vision pathway in natural face perception. The brain was more sharply tuned to subtle expressions over strong one—a “Weber’s law” for facial expressions—which was confirmed in controlled psychophysical experiments. This study leveraged neural recordings during natural social interactions to model neuro-perceptual relationships in an uncontrolled real-world environment, revealed neural coding rules for facial expressions, and demonstrated the perceptual implications of those rules using controlled experimentation.

Critical neurocognitive processes, such as performing natural activities and fluctuations of arousal, take place over minutes-to-days in real-world environments. Dr. Ghuman harnessed 3-12 days of continuous multi-electrode intracranial recordings in twenty humans that engaged in natural activities, including interacting with friends and family, watching TV, sleeping, etc., while under simultaneous neural and video recordings. Applying deep learning and dynamical systems analysis to the data revealed that brain network dynamics predicted neurocognitive phenomena such as circadian rhythm, heart rate, and multiple aspects of behavior (socializing, watching a screen, etc.). Network activity formed a “punctuated equilibrium” of stable states and transitory bursts between them. These transitory bursts coincided with shifts in behavior, such as switching from using a phone to talking to a friend. During these transitions, the brain would rapidly explore several interim states in a highly chaotic and disorganized fashion. Despite this chaos, large-scale dynamics were guided by a consistent set of anatomical networks that slowly modulated their activity in accordance with broad neurophysiological and conscious states. These large-scale dynamics were anchored by a homeostatic-like central attractor involving activation of the default mode network. Together, these findings suggest ways our brains use rapid, chaotic transitions that coalesce into neurocognitive states slowly fluctuating around a stabilizing central equilibrium to balance flexibility and stability during real-world behavior.