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Computational Models of Primary Visual Cortex


Primary visual cortex in higher animals like cats and non-human primates is one of the best characterized cortical areas. Therefore, it serves as a paradigmatic area for understanding visual processing and for understanding cortical computation in general. Here we use computational approaches, which are based on network models of different complexity (rate models vs. spiking models, integrate-and-fire vs. Hodgkin-Huxley models, columnar models vs. map models), in order to characterize the functional organization of visual cortex, to study the dynamics of the cortical network, and to evaluate hypotheses about the mechanisms shaping the response properties of visual cortical neurons. A recent model-based analysis of experimental data provided evidence, that cortical networks may operate in a regime which is close to the transition to self-sustained firing. This finding will serve as one starting point for further investigations.

Acknowledgement: Research was funded by BMBF, DFG, HFSPO, Welcome Trust and the Technische Universität Berlin.

Selected Publications:

Dynamics of Orientation Tuning in Cat V1 Neurons Depend on Location within Layers and Orientation Maps
Citation key Schummers2007
Author Schummers, J. and Cronin, B. and Wimmer, K. and Stimberg, M. and Martin, R. and Obermayer, K. and Koerding, K. and Sur, M.
Pages 145 – 159
Year 2007
DOI 10.3389/neuro.
Journal Frontiers in Neuroscience
Volume 1
Abstract Analysis of the timecourse of the orientation tuning of responses in primary visual cortex (V1) can provide insight into the circuitry underlying tuning. Several studies have examined the temporal evolution of orientation selectivity in V1 neurons, but there is no consensus regarding the stability of orientation tuning properties over the timecourse of the response. We have used reverse-correlation analysis of the responses to dynamic grating stimuli to reexamine this issue in cat V1 neurons. We find that the preferred orientation and tuning curve shape are stable in the majority of neurons; however, more than forty percent of cells show a significant change in either preferred orientation or tuning width between early and late portions of the response. To examine the influence of the local cortical circuit connectivity, we analyzed the timecourse of responses as a function of receptive field type, laminar position and orientation map position. Simple cells are more selective, and reach peak selectivity earlier, than complex cells. There are pronounced laminar differences in the timing of responses: middle layer cells respond faster, deep layer cells have prolonged response decay, and superficial cells are intermediate in timing. The average timing of neurons near and far from pinwheel centers is similar, but there is more variability in the timecourse of responses near pinwheel centers. This result was reproduced in an established network model of V1 operating in a regime of balanced excitatory and inhibitory recurrent connections, confirming previous results. Thus, response dynamics of cortical neurons reflect circuitry based on both vertical and horizontal location within cortical networks.
Bibtex Type of Publication Selected:v1
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