Neural Comp. NEW Faster Access
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
 QUICK SEARCH:   [advanced]


     


This Article
Right arrow Full Text
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Gottschalk, A.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Gottschalk, A.
(Neural Computation. 2002;14:527-542.)
© 2002 The MIT Press


Letter

Derivation of the Visual Contrast Response Function by Maximizing Information Rate

Allan Gottschalk

agottschalk{at}jhmi.edu, Department of Anesthesiology and Critical Care Medicine, Johns Hopkins Medical Institutes, Baltimore, MD 21287, U.S.A.

A graph of neural output as a function of the logarithm of stimulus intensity often produces an S-shaped function, which is frequently modeled by the hyperbolic ratio equation. The response of neurons in early vision to stimuli of varying contrast is an important example of this. Here, the hyperbolic ratio equation with a response exponent of two is derived exactly by considering the balance between information rate and the neural costs of making that information available, where neural costs are a function of synaptic strength and spike rate. The maximal response and semisaturation constant of the neuron can be related to the stimulus ensemble and therefore shift accordingly to exhibit contrast gain control and normalization.




This article has been cited by other articles:


Home page
Neural Comput.Home page
M. S. Falconbridge, R. L. Stamps, and D. R. Badcock
A Simple Hebbian/Anti-Hebbian Network Learns the Sparse, Independent Components of Natural Images
Neural Comput., February 1, 2005; 18(2): 415 - 429.
[Abstract] [Full Text] [PDF]




HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
J COGNITIVE NEUROSCIENCE NEURAL COMPUTATION MIT PRESS JOURNALS
Copyright © 2002 by The MIT Press.