Coordinated optimization of visual cortical maps (II) numerical studies

In the juvenile brain, the synaptic architecture of the visual cortex remains in a state of flux for months after the natural onset of vision and the initial emergence of feature selectivity in visual cortical neurons. I
In the juvenile brain, the synaptic architecture of the visual cortex remains in a state of flux for months after the natural onset of vision and the initial emergence of feature selectivity in visual cortical neurons. It is an attractive hypothesis that visual cortical architecture is shaped during this extended period of juvenile plasticity by the coordinated optimization of multiple visual cortical maps such as orientation preference (OP), ocular dominance (OD), spatial frequency, or direction preference. In part (I) of this study we introduced a class of analytically tractable coordinated optimization models and solved representative examples, in which a spatially complex organization of the OP map is induced by interactions between the maps. We found that these solutions near symmetry breaking threshold predict a highly ordered map layout. Here we examine the time course of the convergence towards attractor states and optima of these models. In particular, we determine the timescales on which map optimization takes place and how these timescales can be compared to those of visual cortical development and plasticity. We also assess whether our models exhibit biologically more realistic, spatially irregular solutions at a finite distance from threshold, when the spatial periodicities of the two maps are detuned and when considering more than 2 feature dimensions. We show that, although maps typically undergo substantial rearrangement, no other solutions than pinwheel crystals and stripes dominate in the emerging layouts. Pinwheel crystallization takes place on a rather short timescale and can also occur for detuned wavelengths of different maps. Our numerical results thus support the view that neither minimal energy states nor intermediate transient states of our coordinated optimization models successfully explain the architecture of the visual cortex. We discuss several alternative scenarios that may improve the agreement between model solutions and biological observations.
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Metadaten
Author:Lars Reichl, Dominik Heide, Siegrid Löwel, Justin C. Crowley, Matthias Kaschube, Fred Wolf
URN:urn:nbn:de:hebis:30:3-274972
DOI:http://dx.doi.org/10.1371/journal.pcbi.1002756
ISSN:1553-7358
ISSN:1553-734X
Parent Title (English):PLoS Computational Biology
Publisher:Public Library of Science
Place of publication:San Francisco, Calif.
Document Type:Article
Language:English
Date of Publication (online):2012/11/08
Date of first Publication:2012/11/08
Publishing Institution:Univ.-Bibliothek Frankfurt am Main
Release Date:2012/11/09
Volume:8
Issue:(11): e1002756
Pagenumber:26
First Page:1
Last Page:26
Note:
Copyright: © 2012 Reichl et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Institutes:Frankfurt Institute for Advanced Studies (FIAS)
Dewey Decimal Classification:570 Biowissenschaften; Biologie
Sammlungen:Universitätspublikationen
Sondersammelgebiets-Volltexte
Licence (German):License LogoCreative Commons - Namensnennung 3.0

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