Efficient laminar-distributed interactions and orientation selectivity in the mouse V1 cortical column

Abstract

The emergence of orientation selectivity in the visual cortex is a well-known phenomenon in neuroscience, but the details of such emergence and the role of different cortical layers and cell types, particularly in rodents which lack a topographical organization of orientation-selectivity (OS) properties, are less clear. To tackle this question, we use an existing biologically detailed model of the mouse V1 cortical column, which is constrained by existing connectivity data across cortical layers and between pyramidal, PV, SST and VIP cell types. Using this model as a basis, we implemented activity-dependent structural plasticity induced by stimulation with orientated drifting gratings, leading to a good match of tuning properties of pyramidal cells with experimentally observed OS laminar distribution, their evoked firing rate and tuning width. We then employed a mean-field model to uncover the role of co-tuned subnetworks in laminar signal propagation and explain the effects of intra- and inter- laminar coupling distributions. Our plasticity-induced modified model and mean-field model were able to explain both the excitatory enhancement through co-tuned subnetworks and inter-laminar disynaptic inhibition. Overall, our work highlights the importance of the clustering of neural selectivity features for effective excitatory transmission in cortical circuits.

邹立诚

Master student of neuroscience

My research interest focus on the application of mathematics and theoretical physices to neuroscience, especially in the analysis of neuronal networks and the computational mechanisms of long-term memory and visual encoding.