On the functional role of noise correlations in the nervous system

Neurons are known to respond to external stimuli in a noisy manner. This response variability is often correlated across the neural population. However, the functional role of these noise correlations is still unclear. In this paper, Fisher information is used to analyze the effects of noise correlations on the accuracy with which a neural population encodes a stimulus. The existence of limited-range correlations of the type found in cortical tissue yields a saturation of the Fisher information content as a function of the population size only for an additive noise model. We also show that random variability in the correlation coefficient within a neural population can considerably improve the average encoding quality. This means that diversity in the correlations, as found empirically, could be exploited for improving stimulus representation. [Copyright &y& Elsevier]