title: Five key factors determining pairwise correlations in visual cortex.
abstract: The responses of cortical neurons to repeated presentation of a stimulus are highly variable, yet correlated. These "noise correlations" reflect a low-dimensional structure of population dynamics. Here, we examine noise correlations in 22,705 pairs of neurons in primary visual cortex (V1) of anesthetized cats, during ongoing activity and in response to artificial and natural visual stimuli. We measured how noise correlations depend on 11 factors. Because these factors are themselves not independent, we distinguished their influences using a nonlinear additive model. The model revealed that five key factors play a predominant role in determining pairwise correlations. Two of these are distance in cortex and difference in sensory tuning: these are known to decrease correlation. A third factor is firing rate: confirming most earlier observations, it markedly increased pairwise correlations. A fourth factor is spike width: cells with a broad spike were more strongly correlated amongst each other. A fifth factor is spike isolation: neurons with worse isolation were more correlated, even if they were recorded on different electrodes. For pairs of neurons with poor isolation, this last factor was the main determinant of correlations. These results were generally independent of stimulus type and timescale of analysis, but there were exceptions. For instance, pairwise correlations depended on difference in orientation tuning more during responses to gratings than to natural stimuli. These results consolidate disjoint observations in a vast literature on pairwise correlations and point towards regularities of population coding in sensory cortex.
authors.affiliation: COMPLeX, London, United Kingdom; Gatsby Computational Neuroscience Unit, London, United Kingdom; and Institute of Ophthalmology, University College London, London, United Kingdom schulz.dpa@gmail.com.
authors.forename: David P A
authors.initials: DP
authors.lastname: Schulz
authors.affiliation: Gatsby Computational Neuroscience Unit, London, United Kingdom; and.
authors.forename: Maneesh
authors.initials: M
authors.lastname: Sahani
authors.affiliation: Institute of Ophthalmology, University College London, London, United Kingdom.
authors.forename: Matteo
authors.initials: M
authors.lastname: Carandini
mesh_terms: D000200:Action Potentials; D000818:Animals; D002415:Cats; D004569:Electroencephalography; D005260:Female; D008839:Microelectrodes; D008959:Models, Neurological; D009474:Neurons / Q000502:physiology*; D017711:Nonlinear Dynamics; D010775:Photic Stimulation; D012815:Signal Processing, Computer-Assisted; D014793:Visual Cortex / Q000502:physiology*; D014796:Visual Perception / Q000502:physiology*
keywords: functional connectivity; natural stimuli; sensory cortex; spontaneous activity; variability