Abstract
Understanding the role of the different types of inhibitory interneurons in cortical computations is central to elucidating how the neocortex processes sensory information. The emergence of orientation tuning in primate primary visual cortex (V1) is a canonical model for studying how cortical sensory circuits and inhibitory interneurons compute relevant stimulus features. The selective feedforward convergence of non-orientation-selective thalamic afferents establishes initial orientation tuning in the granular V1 input layer. As signals propagate through the cortical microcircuit, orientation tuning sharpens in extra-granular layers, yet the underlying mechanisms and the contribution of specific inhibitory neuron subtypes within V1 remain unresolved. To study the role of the largest cortical inhibitory neuron subclass, parvalbumin-expressing ( PV (+) ) interneurons, in this V1 computation, we combined laminar extracellular recordings with bidirectional optogenetic manipulations of PV (+) cells in marmoset V1. Our results reveal a striking laminar specificity: in granular layers, PV (+) cells implement divisive/ multiplicative linear gain control, whereas in extra-granular layers they exert tuned nonlinear suppression that enhances orientation tuning. Computational modeling suggests that PV (+) neurons can control gain by changing a neuron's spiking threshold, and orientation tuning by changing a neuron's input noise, which regulates the neuron's input-output function. Our findings reconcile divergent results from previous rodent studies and establish a framework for understanding layer-dependent inhibitory computations in the primate cortex.