Distributional Population Codes and Multiple Motion Models

Abstract

Most theoretical and empirical studies of population codes make the assumption that underlying neuronal activities is a unique and unambiguous value of an encoded quantity. However, population activities can contain additional information about such things as multiple values of or uncertainty about the quantity. We have pre(cid:173) viously suggested a method to recover extra information by treat(cid:173) ing the activities of the population of cells as coding for a com(cid:173) plete distribution over the coded quantity rather than just a single value. We now show how this approach bears on psychophys(cid:173) ical and neurophysiological studies of population codes for mo(cid:173) tion direction in tasks involving transparent motion stimuli. We show that, unlike standard approaches, it is able to recover mul(cid:173) tiple motions from population responses, and also that its output is consistent with both correct and erroneous human performance on psychophysical tasks.