The visual system encodes large amounts of information about the physical world with limited resources. Encoding is more efficient when the responses of neurons are less correlated with each other, but the mechanisms that achieve decorrelation in the early visual system remain largely unknown. Here, Ahmad's analyses show evidence that response properties in dLGN and V1 lead to population-wide fluctuations in the balance of enhancement and suppression that dynamically reduce correlations between low and high SFs. These results suggest that SF information is encoded most efficiently during a population-wide transition from enhancement to suppression and highlight the importance of geniculocortical circuits in encoding rich visual information.

Congratulations, Ahmad!