Neuronal variability reflects probabilistic inference tuned to natural image statistics.

ABSTRACT: Neuronal activity in sensory cortex fluctuates over time and across repetitions of the same input. This variability is often considered detrimental to neural coding. The theory of neural sampling proposes instead that variability encodes the uncertainty of perceptual inferences. In primary visual cortex (V1), modulation of variability by sensory and non-sensory factors supports this view. However, it is unknown whether V1 variability reflects the statistical structure of visual inputs, as would be required for inferences correctly tuned to the statistics of the natural environment. Here we combine analysis of image statistics and recordings in macaque V1 to show that probabilistic inference tuned to natural image statistics explains the widely observed dependence between spike count varian

SUBMITTER: Festa D 

PROVIDER: S-EPMC8206154 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature