Neural mechanisms of motion detection, integration, and segregation: from biology to artificial image processing systems

Authors:
Jan D. Bouecke;Emilien Tlapale;Pierre Kornprobst;Heiko Neumann
Affiliations:
Faculty of Engineering and Computer Sciences, Institute for Neural Information Processing, Ulm University, Ulm, Germany;Institut National de Recherche en Informatique et en Automatique, Sophia Antipolis Cedex, France;Institut National de Recherche en Informatique et en Automatique, Sophia Antipolis Cedex, France;Faculty of Engineering and Computer Sciences, Institute for Neural Information Processing, Ulm University, Ulm, Germany
Venue:
EURASIP Journal on Advances in Signal Processing - Special issue on biologically inspired signal processing: analyses, algorithms and applications
Year:
2011

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Abstract

Object motion can be measured locally by neurons at different stages of the visual hierarchy. Depending on the size of their receptive field apertures they measure either localized or more global configurationally spatiotemporal information. In the visual cortex information processing is based on the mutual interaction of neuronal activities at different levels of representation and scales. Here, we utilize such principles and propose a framework for modelling neural computational mechanisms of motion in primates using biologically inspired principles. In particular, we investigate motion detection and integration in cortical areas V1 and MT utilizing feedforward and modulating feedback processing and the automatic gain control through center-surround interaction and activity normalization. We demonstrate that the model framework is capable of reproducing challenging data from experimental investigations in psychophysics and physiology. Furthermore, the model is also demonstrated to successfully deal with realistic image sequences from benchmark databases and technical applications.