サル一次視覚野の層状回路における神経応答変動のサイズ調整

Surround suppression and neural response variability are widespread cortical phenomena thought to facilitate and impede, respectively, information processing and perception. Because manipulations that elicit neural response suppression often quench variability, it has been proposed that these two phenomena share a common origin. However, the relationship between surround suppression and variability has not been systematically examined. 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 interact and influence laminar processing, we used laminar electrophysiological 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 both individual and shared variability relative to pre-stimulus baseline. Expanding the stimulus beyond the RF, into the near RF surround, further decreased variability in infragranular layers, but had little effect in granular and supragranular layers. In contrast, large stimuli extending into the far RF surround increased both individual 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, stimuli smaller than the RF could increase variability above baseline values, particularly in granular and infragranular layers. Our results indicate that surround suppression and variability are not governed by a single mechanism. Instead, multiple laminar-specific circuits and mechanisms shape variability, highlighting the need for revised models of neural response variability in cortical processing.