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UP: Lateral Interactions in the Cortex: Structure and Function
Associative Decorrelation Dynamics in Visual Cortex
Dawei W. Dong
Computational Neuroscience Laboratory
The Rockefeller University
1230 York Avenue
New York, NY 10021-6399
dawei@hope.caltech.edu
Abstract
This paper outlines a dynamic theory of development and adaptation in
neural networks with feedback connections. Given input ensemble, the
connections change in strength according to an associative learning rule
and approach a stable state where the neuronal outputs are decorrelated.
We apply this theory to primary visual cortex and examine the
implications of the dynamical decorrelation of the activities of
cortical cells. The orientation selective columns are developed with
both feedforward and feedback connection changes and with natural images
as inputs. The feedback connections form columnar structures that
regulate the development of orientation selectivity of feedforward
connections. The theory gives a unified and quantitative account of the
development of both feedforward and feedback connections of orientation
selective cells which are shown to be able to explain the psychophysical
experiments on orientation contrast and orientation adaptation. Using
only one parameter, we achieve good agreements between the theoretical
predictions and the experimental data.
Next: Introduction
UP: Lateral Interactions in the Cortex: Structure and Function
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