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Neurons in primary visual cortex (V1) show a remarkable functional specificity in their pre- and postsynaptic partners. Recent work has revealed a variety of wiring biases describing how the short- and long-range connections of V1 neurons relate to their tuning properties. However, it is less clear whether these connectivity rules are based on some underlying principle of cortical organization. Here, we show that the functional specificity of V1 connections emerges naturally in a recurrent neural network optimized to predict upcoming sensory inputs for natural visual stimuli. This temporal prediction model reproduces the complex relationships between the connectivity of V1 neurons and their orientation and direction preferences, the tendency of highly connected neurons to respond more similarly to natural movies, and differences in the functional connectivity of excitatory and inhibitory V1 populations. Together, these findings provide a principled explanation for the functional and anatomical properties of early sensory cortex.

Original publication

DOI

10.1016/j.cub.2024.11.073

Type

Journal article

Journal

Curr Biol

Publication Date

06/01/2025

Keywords

computational model, connectivity, direction selectivity, excitatory, functional specificity, inhibitory, neural network, orientation selectivity, primary visual cortex, temporal prediction