RT Journal Article
SR Electronic
T1 A neural basis of probabilistic computation in visual cortex
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 365973
DO 10.1101/365973
A1 Walker, Edgar Y.
A1 James Cotton, R.
A1 Ma, Wei Ji
A1 Tolias, Andreas S.
YR 2019
UL http://biorxiv.org/content/early/2019/04/25/365973.abstract
AB Bayesian models of behavior suggest that organisms represent uncertainty associated with sensory variables. However, the neural code of uncertainty remains elusive. A central hypothesis is that uncertainty is encoded in the population activity of cortical neurons in the form of likelihood functions. We studied the neural code of uncertainty by simultaneously recording population activity from the primate visual cortex during a visual categorization task in which trial-to-trial uncertainty about stimulus orientation was relevant for the decision. We decoded the likelihood function from the trial-to-trial population activity and found that it predicted decisions better than a point estimate of orientation. This remained true when we conditioned on the true orientation, suggesting that internal fluctuations in neural activity drive behaviorally meaningful variations in the likelihood function. Our results establish the role of population-encoded likelihood functions in mediating behavior, and provide a neural underpinning for Bayesian models of perception.