How is luminance information passed into the cortex: emergent multifunctional behavior of a simple cell model

Matthias S. Keil; Gabriel Cristobal

doi:10.1117/12.367687

1 November 1999 How is luminance information passed into the cortex: emergent multifunctional behavior of a simple cell model

Matthias S. Keil, Gabriel Cristobal

Author Affiliations +

Proceedings Volume 3812, Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation II; (1999) https://doi.org/10.1117/12.367687
Event: SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, 1999, Denver, CO, United States

Abstract

In modeling brightness perception, one problem of high biological relevance is how luminance information is transmitted into the primary visual cortex. This is especially interesting in the light of recent neurophysiological studies, which suggest that simple cells are responding shallowly to homogeneous illuminated surfaces. This indicates that simple cells possess far more functional complexity as the wide-spread notion of mere line and edge detectors. Here we present new neural circuits for modeling even and odd simple cells, capable of transmitting brightness information without using an extra `luminance- channel'. Although these circuits taken for themselves can not be regarded yet as a full brightness model, however, they might gain some insight in why the visual system is using certain processing strategies. These include e.g. the segregation in ON and OFF channels and the mutual inhibition of simple cell pairs which are in anti-phase relation. These simple cell circuits turn out to be robust against noise, and thus might find its application in a border detection scheme, beside of being a building block for a more sophisticated brightness-model.

Citation Download Citation

Matthias S. Keil and Gabriel Cristobal "How is luminance information passed into the cortex: emergent multifunctional behavior of a simple cell model", Proc. SPIE 3812, Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation II, (1 November 1999); https://doi.org/10.1117/12.367687

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