Size tuning of neural response variability in laminar circuits of macaque primary visual cortex

Abstract

Surround suppression and neural response variability are two widespread cortical phenomena thought to facilitate and impede, respectively, information processing and perception. Typically, manipulations that elicit neural response suppression quench variability, an observation that has led some to suggest that these two phenomena may share a common origin. However, few studies have systematically examined the relationship between surround suppression and variability. Surround suppression is mediated by multiple circuits and mechanisms that depend on the size of the sensory stimulus, and cortical layer. Variability is also laminar dependent. To understand how surround suppression and variability may influence laminar processing, here we have used electrophysiological laminar recordings to examine how neural response variability and the shared variability among neurons are modulated by visual stimulus size across the layers of macaque primary visual cortex (V1). We find that surround suppression does not always quench variability. Instead, variability is tuned for stimulus size in a layer-dependent manner. In all layers, stimulation of the receptive field (RF) reduced neural response variability, and the shared variability among neurons, relative to their pre-stimulus values. As the stimulus was enlarged beyond the RF, to involve the near RF-surround, both neural response variability and shared variability further decreased in infragranular layers, but did not change in granular and supragranular layers. In contrast, larger stimuli involving the far RF-surround increased both neural response variability and shared variability, relative to their value for a stimulus matched to the RF size, in supragranular layers, but decreased them or did not change them in granular and infragranular layers. Surprisingly, we also found that visual stimuli smaller than the RF could increase variability relative to baseline values, particularly in granular and infragranular layers. Our results point to multiple laminar-specific circuits and mechanisms as the source of variability, and call for new models of neural response variability.