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We investigate a possible functional role of glial cells as information routing devices of the cerebral cortex. On the one hand, functionally motivated models of neural information processing were lately suggested which rely on short-term changes of connections between neural modules to dynamically route neural activity. Although successful in practice, the(More)
One way to handle the perception of images that change in position (or size, orientation or deformation) is to invoke rapidly changing fiber projections to project images into a fixed format in a higher cortical area. We propose here a model for the ontogenesis of the necessary control structures. For simplicity we limit ourselves to fiber projections(More)
We here are pointing out a basically well-known pathway to the analysis of self-organizing systems that is now well in reach of numerical methods. Systems of coupled nonlinear differential equations are decomposed into normal modes, are reduced by adiabatic elimination of stable modes to a much smaller system of unstable modes and their nonlinear(More)
Rapid self-organization of a mapping between two patterns plays an important role in various visual tasks such as object recognition. This task is di cult because of the variations we have to deal with, such as shift, scale and orientation. Dynamic Link Matching (DLM) [1] is a matching process that is ideal in dealing with many of the variations, but it is(More)
A well established method to analyze dynamical systems described by coupled nonlinear differential equations is to determine their normal modes and reduce the dynamics, by adiabatic elimination of stable modes, to a much smaller system for the amplitudes of unstable modes and their nonlinear interactions. So far, this analysis is possible only for idealized(More)
Introduction We study the problem of object recognition invariant to transformations, such as translation, rotation and scale. A system is underdetermined if its degrees of freedom (number of possible transformations and potential objects) exceed the available information (image size). The regularization theory solves this problem by adding constraints [1].(More)