Literature DB >> 18987857

Steps toward numerical mode analysis of organizing systems.

Junmei Zhu1, Christoph von der Malsburg.   

Abstract

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 symmetric model systems. We aim to build a framework in which realistic systems with less symmetry can be analyzed automatically. In this paper we present a first example of mode analysis with the assistance of numerical computation. Our method is illustrated using a model system for the ontogenesis of retinotopy, and the results reproduce those from theoretical analysis precisely. Aspects of organization generalized from this model system are discussed.

Mesh:

Year:  2008        PMID: 18987857     DOI: 10.1007/s00285-008-0233-8

Source DB:  PubMed          Journal:  J Math Biol        ISSN: 0303-6812            Impact factor:   2.259


  7 in total

1.  An amplitude equation approach to contextual effects in visual cortex.

Authors:  Paul C Bressloff; Jack D Cowan
Journal:  Neural Comput       Date:  2002-03       Impact factor: 2.026

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Authors: 
Journal:  Phys Rev Lett       Date:  1990-02-19       Impact factor: 9.161

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Authors:  M J Lyons; L G Harrison
Journal:  Dev Dyn       Date:  1992-11       Impact factor: 3.780

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Authors:  P Arcuri; J D Murray
Journal:  J Math Biol       Date:  1986       Impact factor: 2.259

Review 5.  A marker induction mechanism for the establishment of ordered neural mappings: its application to the retinotectal problem.

Authors:  D J Willshaw; C von der Malsburg
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  1979-11-01       Impact factor: 6.237

6.  A mathematical theory of visual hallucination patterns.

Authors:  G B Ermentrout; J D Cowan
Journal:  Biol Cybern       Date:  1979-10       Impact factor: 2.086

7.  Neurons with graded response have collective computational properties like those of two-state neurons.

Authors:  J J Hopfield
Journal:  Proc Natl Acad Sci U S A       Date:  1984-05       Impact factor: 11.205

  7 in total

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