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Neural Computation

May 15, 1999, Vol. 11, No. 4, Pages 919-934
(doi: 10.1162/089976699300016502)
© 1999 Massachusetts Institute of Technology
Spatiotemporal Coding in the Cortex: Information Flow-Based Learning in Spiking Neural Networks
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We introduce a learning paradigm for networks of integrate-and-fire spiking neurons that is based on an information-theoretic criterion. This criterion can be viewed as a first principle that demonstrates the experimentally observed fact that cortical neurons display synchronous firing for some stimuli and not for others. The principle can be regarded as the postulation of a nonparametric reconstruction method as optimization criteria for learning the required functional connectivity that justifies and explains synchronous firing for binding of features as a mechanism for spatiotemporal coding. This can be expressed in an information-theoretic way by maximizing the discrimination ability between different sensory inputs in minimal time.