An emergent model of orientation selectivity in cat visual cortical simple cells

Abstract

It is well known that visual cortical neurons respond vigorously to a limited range of stimulus orientations, while their primary afferent inputs, neurons in the lateral geniculate nucleus (LGN), respond well to all orientations. Mechanisms based on intracortical inhibition and/or converging thalamocortical afferents have previously been suggested to underlie the generation of cortical orientation selectivity; however, these models conflict with experimental data. Here, a 1:4 scale model of a 1700 microns by 200 microms region of layer IV of cat primary visual cortex (area 17) is presented to demonstrate that local intracortical excitation may provide the dominant source of orientation-selective input. In agreement with experiment, model cortical cells exhibit sharp orientation selectivity despite receiving strong iso-orientation inhibition, weak cross-orientation inhibition, no shunting inhibition, and weakly tuned thalamocortical excitation. Sharp tuning is provided by recurrent cortical excitation. As this tuning signal arises from the same pool of neurons that it excites, orientation selectivity in the model is shown to be an emergent property of the cortical feedback circuitry. In the model, as in experiment, sharpness of orientation tuning is independent of stimulus contrast and persists with silencing of ON-type subfields. The model also provides a unified account of intracellular and extracellular inhibitory blockade experiments that had previously appeared to conflict over the role of inhibition. It is suggested that intracortical inhibition acts nonspecifically and indirectly to maintain the selectivity of individual neurons by balancing strong intracortical excitation at the columnar level.

Local networks in visual cortex and their influence on neuronal responses and dynamics

“…However, there are also numerous features of orientation tuning that this model cannot explain ( [14,21,44,52]; see [63,65] for a review). Several computational models have proposed alternate schemes, based primarily on recurrent amplification of inputs to cortex, that can largely explain the experimental data without recourse to a strict arrangement of thalamocortical projections required by the feedforward model [7,17,64]. Some models that rely entirely on intracortical connections to produce tuning can produce orientation selectivity without any bias in the thalamocortical input [22].…”

A Continuous Attractor Network Model Without Recurrent Excitation: Maintenance and Integration in the Head Direction Cell System

“…Continuous attractor network models (Amari, 1977;Ermentrout, 1998) have been proposed to account for selectivity properties of sensory (Ben-Yishai et al, 1995;Somers et al, 1995;Hansel and Sompolinsky, 1998) and motor (Lukashin and Georgopoulos, 1993) systems, for maintenance of a continuous variable in working memory in prefrontal and parietal cortices (Camperi and Wang, 1998;Compte et al, 2000;Laing and Chow, 2001;Gutkin et al, 2001), and for properties of hippocampal place cells (Tsodyks and Sejnowski, 1995;Samsonovich and McNaughton, 1997;Redish and Touretzky, 1997;Battaglia and Treves, 1998;Kali and Dayan, 2000).…”

Functional organization of excitatory synaptic strength in primary visual cortex

“…This circuit architecture-comprising strong recurrent excitation within ensembles of neurons with similar RFs-may additionally amplify (and perhaps prolong 25 ) populationlevel responses to particular sensory stimuli 19,20,[26][27][28][29] , and thus promote effective information transmission to multiple postsynaptic targets. In contrast, the matrix of more numerous, weaker connections, which only generate a small fraction of total excitation in the L2/3 network, may facilitate local contextual interactions and serve as a substrate for plasticity-for example, when particular visual feature combinations become behaviourally relevant.…”