Spatiotemporal Coding in the Cortex: Information Flow-Based Learning in Spiking Neural Networks
Abstract
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.
Cite
Text
Deco and Schürmann. "Spatiotemporal Coding in the Cortex: Information Flow-Based Learning in Spiking Neural Networks." Neural Computation, 1999. doi:10.1162/089976699300016502Markdown
[Deco and Schürmann. "Spatiotemporal Coding in the Cortex: Information Flow-Based Learning in Spiking Neural Networks." Neural Computation, 1999.](https://mlanthology.org/neco/1999/deco1999neco-spatiotemporal/) doi:10.1162/089976699300016502BibTeX
@article{deco1999neco-spatiotemporal,
title = {{Spatiotemporal Coding in the Cortex: Information Flow-Based Learning in Spiking Neural Networks}},
author = {Deco, Gustavo and Schürmann, Bernd},
journal = {Neural Computation},
year = {1999},
pages = {919-934},
doi = {10.1162/089976699300016502},
volume = {11},
url = {https://mlanthology.org/neco/1999/deco1999neco-spatiotemporal/}
}