Emergence of Probabilistic Representation in the Neural Network of Primary Visual Cortex

Abstract

During the early development of mammalian visual system, the distribution of neuronal preferred orientations in the primary visual cortex (V1) gradually shifts to match the major orientation features of an environment, achieving optimal representation of the environment. By combining the computational modeling and experimental electrophysiological recording, we provide a circuitry plasticity mechanism that underlies the developmental emergence of such matched representation in the visual cortical network. Specifically, in a canonical circuit of densely interconnected pyramidal cells and inhibitory parvalbumin-expressing (PV+) fast-spiking interneurons in the V1 layer 2/3, our model successfully simulates the experimental observations and further reveals that the non-uniform inhibition, mediated by local interneurons, exerts a key role in shaping the network representation through spike timing-dependent synaptic modifications. The experimental results confirm that PV+ interneurons in the V1 are capable of providing such non-uniform inhibition during a short period after the vision onset. Thus, our study elucidates a circuitry mechanism for acquisition of the prior knowledge of environment for optimal inference in sensory neural system.