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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:

The Operating Regime of Local Computations in Primary Visual Cortex
Citation key Stimberg2009
Author Stimberg, M. and Wimmer, K. and Martin, R. and Schwabe, L. and Marino, J. and Schummers, J. and Lyon, D. and Sur, M. and Obermayer, K.
Pages 2166 – 2180
Year 2009
DOI 10.1093/cercor/bhn240
Journal Cerebral Cortex
Volume 19
Number 9
Publisher Oxford Journals
Abstract In V1, local circuitry depends on the position in the orientation map: close to pinwheel centers recurrent inputs show variable orientation preferences; within iso-orientation domains inputs are relatively uniformly tuned. Physiological properties such as cell's membrane potentials, spike outputs, and temporal characteristics change systematically with map location. We investigate in a firing rate and a Hodgkin-Huxley network model what constraints these tuning characteristics of V1 neurons impose on the cortical operating regime. Systematically varying the strength of both recurrent excitation and inhibition, we test a wide range of model classes and find the likely models to account for the experimental observations. We show that recent intracellular and extracellular recordings from cat V1 provide the strongest evidence for a regime where excitatory and inhibitory recurrent inputs are balanced and dominate the feed-forward input. Our results are robust against changes in model assumptions such as spatial extent and strength of lateral inhibition. Intriguingly, the most likely recurrent regime is in a region of parameter space where small changes have large effects on the network dynamics, and it is close to a regime of ''runaway excitation``, where the network shows strong self-sustained activity. This could make the cortical response particularly sensitive to modulation.
Bibtex Type of Publication Selected:main selected:v1 selected:publications
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