Emergent Orientation Selectivity from Random Networks in Mouse Visual Cortex

Jagruti J Pattadkal,German Mato,Carl Van Vreeswijk,Nicholas J Priebe,David Hansel

doi:10.1016/j.celrep.2018.07.054

Abstract

SUMMARYThe connectivity principles underlying the emergence of orientation selectivity in primary visual cortex (V1) of mammals lacking an orientation map (such as rodents and lagomorphs) are poorly understood. We present a computational model in which random connectivity gives rise to orientation selectivity that matches experimental observations. The model predicts that mouse V1 neurons should exhibit intricate receptive fields in the two-dimensional frequency domain, causing a shift in orientation preferences with spatial frequency. We find evidence for these features in mouse V1 using calcium imaging and intracellular whole-cell recordings.

Highlights

Since its initial description by Hubel and Wiesel (1962), orientation selectivity has served as a platform for studying neocortical computations (Priebe and Ferster, 2012)
We recently showed in a model of rodent V1 that layer 2/3 (L2/3) can inherit orientation selectivity from orientation selective neurons in layer 4 (L4) even if recurrent as well as feedforward (L4 to L2/3) connectivity is random (Hansel and van Vreeswijk, 2012)
The V1 neuron receives ON and OFF thalamic inputs that are sampled on the basis of a Gabor filter: ON and OFF inputs have spatial preferences elongated along the preferred orientation axis and are spatially segregated (Figure 1A)

Summary

Introduction

Since its initial description by Hubel and Wiesel (1962), orientation selectivity has served as a platform for studying neocortical computations (Priebe and Ferster, 2012). Orientation selectivity emerges in V1 of primates and carnivores where a functional organization for this selectivity is observed: neurons are organized in a columnar fashion with shared orientation preference across cortical layers and smooth changes in selectivity along the V1 surface (Hubel and Wiesel, 1977) This functional architecture is the product of the spatial arrangement of ON and OFF thalamocortical inputs that innervate V1 (Kremkow et al, 2016; Lee et al, 2016a) and of the vertical bias of intracortical connectivity (Song et al, 2005). These spatially offset ON and OFF afferents converge on individual V1 neurons to generate receptive fields that are orientation tuned (Alonso et al, 2001) and well described by Gabor functions (Jones and Palmer, 1987) (Figure 1A)

Methods

Results

Discussion

Conclusion