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Models of Neural Systems

PhD Theses

Computational models of contrast and orientation processing in primary visual cortex
Citation key Stimberg2011
Author Marcel Stimberg
Year 2011
School Technische Universität Berlin
Abstract The primary visual cortex (V1) is the first cortical area involved in the processing of visual information, responding to basic features of a visual stimulus like contrast or orientation. Although it is the best studied part of the visual system — and one of the best studied areas in the brain in general — many questions about the involved neural mechanisms remain unclear to date. Anatomical studies show that most of the input received by neurons in V1 does not arise from the earlier visual structures but from within the visual cortex. To a large extent, the response of a neuron is determined by the activity of the surrounding neurons in the local cortical network. In this thesis, we employ computational models of these networks in V1 to shed some light on its contribution to visual processing, comparing the simulation results to electrophysiological recordings from cat V1. We first investigate the role of the local circuitry in the generation of orientation selectivity. Orientation preferences of neurons in V1 of higher mammals are not distributed randomly but vary continuously resulting in an orientation map structure. By systematically exploring two classes of network models we show that the experimentally observed dependence of tuning properties on position in this map is best explained in a network that operates in a strongly recurrent regime, where recurrent excitatory and inhibitory inputs are approximately balanced and dominate the afferent input. These results are confirmed in a second study, where we show that such a network can also explain observed differences in the variability of temporal responses. We then focus on another aspect of input transformation in V1, the non-linear normalization of cell responses: Instead of consistently increasing the response with the contrast of a stimulus, responses of cortical cells saturate well below the maximal levels that would be possible physiologically. In addition, the response to two stimuli at the same position in the visual field is not linearly added but typically smaller than the sum of the responses to the two stimuli presented alone. We demonstrate how such normalization can arise from the combination of afferent input properties with the modulation provided by the local cortical network. Due to the strong influence of the network, the amount of this normalization can show a strong dependence on the position in the local orientation map. Finally, we study the influence of the local network on the response modulation caused by stimuli presented outside of the classical receptive field of a neuron, i. e. by stimuli that do not elicit a response when presented alone. These modulations have their origin outside of the local network and are propagated via long-range connections or via feedback from higher areas. While we explicitly do not include any direct dependence of this modulatory input on the map position, the final processing of the surround influences happens in the local recurrent circuit, leading to differences in the net modulation between cells at different map positions. This processing by the local network then also explains experimentally observed differences in the orientation specificity of the surround influence.
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