Neural spike statistics modify the impact of background noise

Neural populations in the neocortex typically encode multiple stimulus feat ures, e.g., position, brightness, contrast, and orientation of a visual sti mulus in the case of cells in area 17. Here, we perform a Fisher informatio n analysis of the encoding accuracy of a neural population which is sensiti ve to D stimulus features. The neurons are assumed to exhibit a non-vanishi ng level of baseline activity. It is shown that the encoding accuracy decre ases drastically with D if the spike count variance depends on the mean spi ke count, as is the case for Poissonian spike statistics. The need to reduc e the susceptibility to background noise thus poses severe restrictions on the neural firing statistics or the number of encoded stimulus features. Th e results hold for uncorrelated as well as for correlated activity in the n eural population. (C) 2001 Elsevier Science B.V. All rights reserved.