A neural mechanism of feature binding based on the dynamical map theory in distributed coding scheme

In order to understand a neural basis for the binding problem, we propose a neural network model that is constructed based on dynamical map theory. In the architecture, object stimulation activates sets of neurons of the different sensory networks, where all the features of an object are stored as p...

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Bibliographic Details
Published in:Neurocomputing Vol. 26; pp. 729 - 734
Main Authors: Hoshino, Osamu, Kashimori, Yoshiki, Kambara, Takeshi
Format: Journal Article
Language:English
Japanese
Published: Elsevier B.V 01.06.1999
Elsevier BV
Subjects:
Cells
Computer simulation
Dynamical map theory
Feature binding
Feature extraction
Object association
Object recognition
Object segregation
Problem solving
Random itinerancy
Vision
Object segregation
Dynamical map theory
Feature binding
Object association
Random itinerancy
ISSN:0925-2312, 1872-8286
Online Access:Get full text
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Summary:In order to understand a neural basis for the binding problem, we propose a neural network model that is constructed based on dynamical map theory. In the architecture, object stimulation activates sets of neurons of the different sensory networks, where all the features of an object are stored as point attractors in the networks. Relations among these features are encoded as a point attractor in the integration network. Model simulations show that dynamic linkages among point attractors across the different networks play a key role in solving the binding problem, in which the integration network serves to mediate the binding.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0925-2312
1872-8286
DOI:10.1016/S0925-2312(98)00141-6