Corresponding

Abstract Neural populations in the neocortex typically encode multiple stimulus features, e.g., position, brightness, contrast, and orientation of a visual stimulus in the case of cells in area 17. Here, we perform a Fisher information analysis of the encoding accuracy of a neural population which is sensitive to D stimulus features. The neurons are assumed to exhibit a non-vanishing level of baseline activity. It is shown that the encoding accuracy decreases drastically with D if the spike count variance depends on the mean spike count, as is the case for Poissonian spike statistics. The need to reduce the susceptibility to background noise thus poses severe restrictions on the neural firing statistics or the number of encoded stimulus features. The results hold for uncorrelated as well as for correlated activity in the neural population.