Jennifer Groh

Title: Multiplexing multiple signals in neural codes: new statistical tools and evidence

Abstract: How the brain represents multiple objects is mysterious. Sensory neurons are broadly tuned, producing overlap in the populations of neurons potentially activated by each object in the scene. This overlap raises questions about how distinct information is retained about each item. I will present a novel theory of neural representation, positing that neural signals may interleave representations of individual items across time. Evidence for this theory has come from new statistical tools that overcome the limitations inherent to standard time-and-trial-pooled assessments of activity. This theory has implications for diverse domains of neuroscience, including attention, figure-ground segregation, and grounded cognition.