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Dynamics of information and emergent computation in generic neural microcircuit models (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.

Publication details
Download http://eprints.pascal-network.org/archive/00000491/
Repository PASCAL EPrints (United Kingdom)
Keywords Computational, Information-Theoretic Learning with Statistics
Type Article, NonPeerReviewed
Relation http://eprints.pascal-network.org/archive/00000491/01/153.pdf