Version 1
: Received: 18 July 2019 / Approved: 22 July 2019 / Online: 22 July 2019 (04:44:16 CEST)
How to cite:
Cofre, R.; Videla, L.; Rosas, F. An Introduction to the Non-Equilibrium Steady States of Maximum Entropy Spike Trains. Preprints2019, 2019070230. https://doi.org/10.20944/preprints201907.0230.v1.
Cofre, R.; Videla, L.; Rosas, F. An Introduction to the Non-Equilibrium Steady States of Maximum Entropy Spike Trains. Preprints 2019, 2019070230. https://doi.org/10.20944/preprints201907.0230.v1.
Cite as:
Cofre, R.; Videla, L.; Rosas, F. An Introduction to the Non-Equilibrium Steady States of Maximum Entropy Spike Trains. Preprints2019, 2019070230. https://doi.org/10.20944/preprints201907.0230.v1.
Cofre, R.; Videla, L.; Rosas, F. An Introduction to the Non-Equilibrium Steady States of Maximum Entropy Spike Trains. Preprints 2019, 2019070230. https://doi.org/10.20944/preprints201907.0230.v1.
Abstract
Although most biological processes are characterized by a strong temporal asymmetry, several popular mathematical models neglect this issue. Maximum entropy methods provide a principled way of addressing time irreversibility, which leverages powerful results and ideas from the3literature of non-equilibrium statistical mechanics. This article provides a comprehensive overview of these issues, with a focus in the case of spike train statistics. We provide a detailed account of the5mathematical foundations and work out examples to illustrate the key concepts and results from non-equilibrium statistical mechanics
Keywords
non-equilibrium steady states; maximum entropy principle; spike train statistics; entropy production
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.