A universal power law optimizes energy and representation fidelity in visual adaptation.

ABSTRACT: Sensory systems continuously adapt their responses based on the probability of encountering a given stimulus. In the mouse primary visual cortex (V1), the average population response is a power law of the prior probability of stimuli in the environment. For a given stimulus type (e.g., oriented gratings), the power law's exponent is invariant to changes in statistical environments, enabling predictions of average population responses to new environments. Here, we aim to provide a normative explanation for the power law behavior. We develop an efficient coding model where neurons adjust their firing rates through multi-objective optimization, hypothesizing that the neural population adapts to enhance stimulus detection and discrimination while reducing overall neural activity. We show that

SUBMITTER: Mariani M 

PROVIDER: S-EPMC11974702 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature