Five key factors determining pairwise 1 correlations in visual cortex

16 The responses of cortical neurons to repeated presentation of a stimulus are highly variable, yet 17 correlated. These “noise correlations” reflect a low-dimensional structure of population dynamics. 18 Here, we examine noise correlations in 22,705 pairs of neurons in primary visual cortex (V1) of 19 anesthetized cats, during ongoing activity and in response to artificial and natural visual stimuli. We 20 measured how noise correlations depend on 11 factors. Because these factors are themselves not 21 independent, we distinguished their influences using a nonlinear additive model. The model revealed 22 that five key factors play a predominant role in determining pairwise correlations. Two of these are 23 distance in cortex and difference in sensory tuning: these are known to decrease correlation. A third 24 factor is firing rate: confirming most earlier observations, it markedly increased pairwise correlations. 25 A fourth factor is spike width: cells with a broad spike were more strongly correlated amongst each 26 other. A fifth factor is spike isolation: neurons with worse isolation were more correlated, even if 27 they were recorded on different electrodes. For pairs of neurons with poor isolation, this last factor 28 was the main determinant of correlations. These results were generally independent of stimulus type 29 and timescale of analysis, but there were exceptions. For instance, pairwise correlations depended 30 on difference in orientation tuning more during responses to gratings than to natural stimuli. These 31 results consolidate disjoint observations in a vast literature on pairwise correlations, and point 32 towards regularities of population coding in sensory cortex. 33