PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Dynamics of information and emergent computation in generic neural microcircuit models
Thomas Natschläger and Wolfgang Maass
Neural Networks 2004.

Abstract

We employ an efficient method using Bayesian and linear classifiers for analyzing the dynamics of information in high-dimensional states of generic cortical microcircuit models. It is shown that such recurrent circuits of spiking neurons have an inherent capability to carry out rapid computations on complex spike patterns, merging information contained in the order of spike arrival with previously acquired context information.

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EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
ID Code:491
Deposited By:Wolfgang Maass
Deposited On:26 December 2004