Parametric population representation of retinal location: Neuronal interaction dynamics in cat primary visual cortex

Abstract

Neuronal interactions are an intricate part of cortical information processing generating internal representations of the environment beyond simple one-to-one mappings of the input parameter space. Here we examined functional ranges of interaction processes within ensembles of neurons in cat primary visual cortex. Seven 'elementary' stimuli consisting of small squares of light were presented at contiguous horizontal positions. The population representation of these stimuli was compared to the representation of 'composite' stimuli, consisting of two squares of light at varied separations. Based on receptive field measurements and by application of an Optimal Linear Estimator, the representation of retinal location was constructed as a distribution of population activation (DPA) in visual space. The spatiotemporal pattern of the DPA was investigated by obtaining the activity of each neuron for a sequence of time intervals. We found that the DPA of composite stimuli deviates from the superposition of its components because of distance-dependent (1) early excitation and (2) late inhibition. (3) The shape of the DPA of composite stimuli revealed a distance-dependent repulsion effect. We simulated these findings within the framework of dynamic neural fields. In the model, the feedforward response of neurons is modulated by spatia ranges of excitatory and inhibitory interactions within the population. A single set of model parameters was sufficient to describe the main experimental effects. Combined our results indicate that the spatiotemporal processing of visual stimuli is characterized by a delicate, mutual interplay between stimulus-dependent and interaction-based strategies contributing to the formation of widespread cortical activation patterns.