Associate Professor of Radiology\, Neurosurgery and Biomedical E ngineering
WashU
Shuo Wang\, PhD
Associate Professor of Radiology\, Neurosurgery and Biomedical E
ngineering
WashU
How does the human b rain encode\, differentiate and attend to faces? In this talk\, I will addr ess four core questions: (1) What are the neural computational mechanisms f or general face and object encoding? (2) How do neural representations of f aces change with learning? (3) What are the network mechanisms underlying v isual attention? (4) What are the neural population dynamics underlying vis ual attention? Drawing on human single-neuron recordings and advanced compu tational analyses\, I will present evidence for a novel region-based featur e coding mechanism in the medial temporal lobe (MTL). Specifically\, sparse -coding neurons in the MTL encode visually related faces and objects\, wher eas feature neurons exhibit localized tuning that remains stable across cha nges in identity and familiarity. These findings point to a coding scheme g rounded in visual feature space rather than conceptual identity. I will the n describe a computational pathway by which face and object representations evolve from dense\, feature-based encodings in the ventral temporal cortex (VTC) to sparse\, semantic-based codes in the MTL. This transformation sup ports robust visual discrimination and forms the neural foundation for memo ry and recognition. Learning further sharpens these representations: Repeat ed exposure increases representational distance between similar faces in th e MTL\, reflecting experience-dependent refinement that enhances familiar f ace discrimination. Next\, I will discuss how attention dynamically modulat es neural activity across distributed cortical networks. Attentional engage ment enhances MTL responses to visual targets and is associated with gamma- band synchronization between the MTL and medial frontal cortex (MFC). Disti nct synchronization patterns between the MTL and dorsal anterior cingulate cortex (dACC) support different phases of visual search\, working memory an d decision-making. MTL-MFC synchronization also shapes the geometry of neur al representations\, linking attention to representational dynamics. Finall y\, I will highlight neural population dynamics that support goal-directed visual search. Large-scale recordings from V4\, IT\, OFC and LPFC revealed distinct populations encoding attention and category information. Populatio n activity maintained cue representations across delays\, differentiated ca tegories during search and predicted search efficiency. An orthogonal subsp ace provided a latent structure for sustaining task-relevant information\, while foveal attention enhanced peripheral representations through context- dependent changes in representational geometry. Together\, these dynamics f lexibly coordinated attention\, memory and category representations across search stages. Together\, these findings reveal a unified neural framework for how faces and objects are encoded\, refined through experience and prio ritized through attention\, and how distributed population dynamics orchest rate goal-directed visual search — illuminating the computational architect ure of social visual cognition in the human and non-human primate brain.
CATEGORIES:Seminar Series LOCATION:Neuroscience Research Building Auditorium GEO:38.635602;-90.254892 ORGANIZER;CN="Shea":MAILTO:shea.stewart@wustl.edu URL;VALUE=URI:https://neuroscience.wustl.edu/events/event/partment-of-neuro science-seminar-shuo-wang/ END:VEVENT BEGIN:VTIMEZONE TZID:America/Chicago BEGIN:STANDARD TZOFFSETFROM:-0500 TZOFFSETTO:-0600 DTSTART:20251102T070000 TZNAME:CST END:STANDARD END:VTIMEZONE END:VCALENDAR