Please use this identifier to cite or link to this item: http://dx.doi.org/10.14279/depositonce-7487
Main Title: A Neural Network Model for the Self-Organization of Cortical Grating Cells
Author(s): Bauer, Christoph
Burger, Thomas
Stetter, Martin
Lang, Elmar W.
Type: Article
Language Code: en
Abstract: A neural network model with incremental Hebbian learning of afferent and lateral synaptic couplings is proposed,which simulates the activity-dependent self-organization of grating cells in upper layers of striate cortex. These cells, found in areas V1 and V2 of the visual cortex of monkeys, respond vigorously and exclusively to bar gratings of a preferred orientation and periodicity. Response behavior to varying contrast and to an increasing number of bars in the grating show threshold and saturation effects. Their location with respect to the underlying orientation map and their nonlinear response behavior are investigated. The number of emerging grating cells is controlled in the model by the range and strength of the lateral coupling structure.
URI: https://depositonce.tu-berlin.de//handle/11303/8335
http://dx.doi.org/10.14279/depositonce-7487
Issue Date: 2000
Date Available: 11-Oct-2018
DDC Class: 570 Biowissenschaften; Biologie
Subject(s): self-organization
nonlinearities
Visual Cortex
(Anti-)Hebbian learning
lateral plasticity
License: https://creativecommons.org/licenses/by-nc-nd/3.0/
Journal Title: Zeitschrift für Naturforschung C
Publisher: De Gruyter
Publisher Place: Berlin
Volume: 55
Issue: 3-4
Publisher DOI: 10.1515/znc-2000-3-423
Page Start: 282
Page End: 291
EISSN: 1865-7125
ISSN: 0939-5075
Appears in Collections:Inst. Softwaretechnik und Theoretische Informatik » Publications

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