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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:

Singularities in Primate Orientation Maps
Citation key Obermayer1998
Author Obermayer K., and Blasdel, G.G.
Pages 555 – 576
Year 1997
Journal Neural Computation
Volume 9
Abstract We report the results of an analysis of orientation maps in primate striate cortex with focus on singularities and their distribution. Data were obtained from squirrel monkeys and from macaque monkeys of different age. We find that approximately 80 percent of singularities which are nearest neighbors have opposite sign and that the spatial distribution of singularities differs significantly from a random distribution of points. We do not find, however, evidence for consistent geometric patterns which singularities may form across cortex. Except for a different overall alignment of orientation bands and different periods of repetition, maps obtained from different animals and different ages are found similar with respect to the measures used. Orientation maps are then compared with two different pattern models whic hare currently discussed in the literature: Bandpass-filtered white noise, which very well accounts for the overall map structure, and the FAM-model, which specifies the orientation map by the location of singularities and their properties. The bandpass-filtered noise approach to orientation patterns correctly predicts the sign correlations between singularities and accounts for the deviations in the spatial distribution of singularities away from a random dot pattern. The FAM-model can account for the structure of certain local patches of the orien tation map but not for the whole map. None of the models is completely satisfactory and the structure of the orientation map remains to be fully explained.
Bibtex Type of Publication Selected:v1
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