Sensory noise predicts divisive reshaping of receptive fields.

ABSTRACT: In order to respond reliably to specific features of their environment, sensory neurons need to integrate multiple incoming noisy signals. Crucially, they also need to compete for the interpretation of those signals with other neurons representing similar features. The form that this competition should take depends critically on the noise corrupting these signals. In this study we show that for the type of noise commonly observed in sensory systems, whose variance scales with the mean signal, sensory neurons should selectively divide their input signals by their predictions, suppressing ambiguous cues while amplifying others. Any change in the stimulus context alters which inputs are suppressed, leading to a deep dynamic reshaping of neural receptive fields going far beyond simple surround

SUBMITTER: Chalk M 

PROVIDER: S-EPMC5509365 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature