TU Berlin

Neural Information ProcessingComputational Models of Primary Visual Cortex

Neuronale Informationsverarbeitung

Page Content

to Navigation

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:

Invariant Computations in Local Cortical Networks with Balanced Excitation and Inhibition
Citation key Marino2005
Author Mariño, J. and Schummers, J. and Lyon, D.C. and Schwabe, L. and Beck, O. and Wiesing, P. and Obermayer, K. and Sur, M.
Pages 194 – 201
Year 2005
DOI 10.1038/nn1391
Journal Nature Neuroscience
Volume 8
Abstract Cortical computations critically involve local neuronal circuits. The computations are often invariant across a cortical area, yet are carried out by networks which can vary widely within an area based on its functional architecture. Here, we demonstrate a mechanism by which orientation selectivity is computed invariantly in primary visual cortex across an orientation preference map that provides a wide diversity of local circuits. Visually evoked excitatory and inhibitory synaptic conductances are balanced exquisitely in cortical neurons and thus keep the spike response sharply tuned at all map locations. This functional balance derives from spatially isotropic local connectivity to both excitatory and inhibitory cells. Modelling results demonstrate that such co-variation is a signature of recurrent rather than purely feedforward processing, and that the observed isotropic local circuit is sufficient to generate invariant spike tuning.
Bibtex Type of Publication Selected:main selected:v1 selected:publications
Link to original publication Download Bibtex entry


Quick Access

Schnellnavigation zur Seite über Nummerneingabe