Correlated cortical populations can enhance sound localization performance.

Neurons within cortical populations often evidence some degree of response correlation. Correlation has generally been regarded as detrimental to the decoding performance of a theoretical vector-averaging observer making inferences about the physical world-for example, an observer estimating the location of a sound source. However, if an alternative decoder is considered, in this case a Maximum Likelihood estimator, performance can improve when responses in the population are correlated. Improvement in sound localization performance is demonstrated analytically using Fisher information, and is also shown using Monte Carlo simulations based on recordings from single neurons in cat primary auditory cortex.