Vafaei, A. | Search bioRxiv

bioRxiv2025

Laminar-specific control of response gain and orientation-tuning byparvalbumin-expressing inhibitory interneurons in primate visual cortex

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 neurons spiking threshold, and orientation tuning by changing a neurons input noise, which regulates the neurons 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.

neuroscience↗

bioRxiv2022

V1 receptive field structure contributes to neuronal response latency

The timing of neuronal responses is considered to be important for information transferring and communication across individual neurons. However, the sources of variabilities in the timing of neuronal responses are not well understood and sometimes over-interpreted. A systematic variability in the response latencies of the primary visual cortex has been reported in presence of drifting grating stimulus. Whereas the response latencies are systematically dependent on stimulus orientation. To understand the underlying mechanism of these systematic latencies, we recorded the neuronal response of the cat visual cortex, area 17, and simulated the response latency of V1 neurons, with two geometric models. We showed that outputs of these two models significantly predict the response latencies of the electrophysiology recording during orientation tasks. The periodic patterns created in the raster plots were dependent on the relative position of the stimulus rotation center and the receptive-field sub-regions. We argue the position of stimulus is contributing to systematic response latencies, dependent on drifting orientation. Therefore, we provide a toolbox based on our geometrical model for determining the exact location of RF sub-regions. Our result indicates that a major source of neuronal variability is the lack of fine-tuning in the task parameters. Considering the simplicity of the orientation selectivity task, we argue fine-tuning of stimulus properties is crucial for deduction of neural variability in higher-order cortical areas and understanding their neural dynamics.

neuroscience↗