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 spatial 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.

Temporal Asymmetry in Dark–Bright Processing Initiates Propagating Activity across Primary Visual Cortex

“…We additionally found that response profiles for darkening and brightening were equal in size ( ϭ 1.99 Ϯ 0.1 mm SEM, values along major axis of the Gaussian fits) except for the square brightening on a dark background ( ϭ 1.70 Ϯ 0.09 mm SEM, p ϭ 0.018, two-sided Wilcoxon signed-rank test). This indicates that a smaller pool of neurons is recruited in the latter condition, potentially leading to less effective gain control (Sit et al, 2009) or reduced lateral suppression (Ferster, 1986;Nelson, 1991;Jancke et al, 1999), which in turn may contribute to the generation of larger receptive fields for lights on dark background than observed for opposite contrasts and brighter backgrounds (Kremkow et al, 2014). Altogether, we show that for an identical amount of change in stimulus luminance, population activity in response to stimulus darkening dominated responses to brightening during response rise times followed by earlier decay (Fig.…”

A dynamic model for action understanding and goal-directed imitation

“…Such a spatially organized interaction scheme has been originally proposed to explain localized activation patterns in small pieces of neuronal tissue [58,2]. It has later been applied to model various functionalities in the perceptual and the motor domain (e.g., [41,10,61,37,39]). For the present modeling work, we adopt for each network layer a center-surround organization of recurrent interactions as a well studied mechanism underlying persistent activity patterns.…”

Bilateral Integration of Whisker Information in the Primary Somatosensory Cortex of Rats

“…Although previous studies have provided important insights into the temporal and spatial dynamics of cortical interactions (Simons, 1985;Armstrong-James and George, 1988;Simons and Carvell, 1989;Brumberg et al, 1996;Ghazanfar and Nicolelis, 1997;Jancke et al, 1999), interpretations of these findings are limited because integration ascribed to the cortex may in part be attributable to subcortical processes. Whatever the nature of subcortical processes on ascending whisker information, cortical interactions may be addressed by exploiting the role the corpus callosum plays in integrating sensory information that is lateralized subcortically.…”