Preprint Review Version 1 Preserved in Portico This version is not peer-reviewed

Thermodynamic Formalism in Neuronal Dynamics and Spike Train Statistics

Version 1 : Received: 9 October 2020 / Approved: 12 October 2020 / Online: 12 October 2020 (15:28:38 CEST)

A peer-reviewed article of this Preprint also exists.

Cofré, R.; Maldonado, C.; Cessac, B. Thermodynamic Formalism in Neuronal Dynamics and Spike Train Statistics. Entropy 2020, 22, 1330. Cofré, R.; Maldonado, C.; Cessac, B. Thermodynamic Formalism in Neuronal Dynamics and Spike Train Statistics. Entropy 2020, 22, 1330.

Abstract

The Thermodynamic Formalism provides a rigorous mathematical framework to study quantitative and qualitative aspects of dynamical systems. At its core there is a variational principle and corresponding, in its simplest form, to the Maximum Entropy principle, used as a statistical inference procedure to represent, by specific probability measures (Gibbs measures), the collective behaviour of complex systems. This framework has found applications in different domains of scienThe Thermodynamic Formalism provides a rigorous mathematical framework to study quantitative and qualitative aspects of dynamical systems. At its core there is a variational principle and corresponding, in its simplest form, to the Maximum Entropy principle, used as a statistical inference procedure to represent, by specific probability measures (Gibbs measures), the collective behaviour of complex systems. This framework has found applications in different domains of science, in particular, has been fruitful and influential in neurosciences. In this article, we review how the Thermodynamic Formalism can be exploited in the field of theoretical neuroscience, as a conceptual and operational tool, to link the dynamics of interacting neurons and the statistics of action potentials from either experimental data or mathematical models. We comment on perspectives and open problems in theoretical neuroscience that could be addressed within this formalism.ce, in particular, has been fruitful and influential in neurosciences. In this article, we review how the Thermodynamic Formalism can be exploited in the field of theoretical neuroscience, as a conceptual and operational tool, to link the dynamics of interacting neurons and the statistics of action potentials from either experimental data or mathematical models. We comment on perspectives and open problems in theoretical neuroscience that could be addressed within this formalism.

Keywords

Thermodynamic formalism; neuronal networks dynamics; maximum entropy principle; free energy and pressure; linear response; large deviations, ergodic theory

Subject

Computer Science and Mathematics, Applied Mathematics

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