Paper on Population Coding available

[Stefan Wilke]

Dear Connectionists,

the following preprint is available for downloading:

http://www-neuro.physik.uni-bremen.de/institute/publications/download/swilke/WilkeEurich2001-NeuralComp.pdf

Stefan D. Wilke & Christian W. Eurich
Representational Accuracy of Stochastic Neural Populations. 
Neural Computation, in press.

Abstract:

Fisher information is used to analyze the accuracy with which a neural
population encodes D stimulus features. It turns out that the form of
response variability has a major impact on the encoding capacity and
therefore plays an important role in the selection of an appropriate
neural model. In particular, in the presence of baseline firing, the
reconstruction error rapidly increases with D in the case of Poissonian
noise, but not for additive noise. The existence of limited-range
correlations of the type found in cortical tissue yields a saturation of
the Fisher information content as a function of the population size only
for an additive noise model. We also show that random variability in the
correlation coefficient within a neural population, as found
empirically, considerably improves the average encoding quality.
Finally, the representational accuracy of populations with inhomogeneous
tuning properties, either with variability in the tuning widths or
fragmented into specialized subpopulations, is superior to the case of
identical and radially symmetric tuning curves usually considered in the
literature. 




-- 
Stefan D. Wilke

Institut fuer Theoretische Physik (NW1)
Universitaet Bremen
Postfach 330 440  
D-28334 Bremen, Germany

Phone: +49 (421) 218 4524
WWW  : http://www-neuro.physik.uni-bremen.de/~swilke