Redundancy Scaling for Populations of Neurons
Populations of neurons often respond in a redundant fashion to stimuli. One form of redundancy is multiple neurons reacting to similar stimulus, and another is neurons exciting or inhibiting each other. Measurement data from populations of neurons (in our case, in the auditory system of songbirds) suggests that the amount of redundancy varies greatly from one population to another. The goal of this project is to understand and to distinguish between different neural populations based on their amounts of redundancy. One method to characterize the redundancy in a population of neurons is via the mutual information between the stimulus and the responses of one, two, three, etc. neurons in the considered population. Does this information increase rapidly (suggesting little redundancy between neurons) or slowly (suggesting high redundancy)? In this project, we are developing methods to determine the scaling behavior of redundancy from measurement data.