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Thermodynamic Formalism in Neuronal Dynamics and Spike Train Statistics

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 corresponding, in its simplest form, to the Maximum Entropy principle. It is 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, it 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.
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https://hal.inria.fr/hal-03015686
Contributor : Bruno Cessac <>
Submitted on : Friday, November 20, 2020 - 7:24:43 AM
Last modification on : Monday, November 23, 2020 - 5:57:01 PM

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  • HAL Id : hal-03015686, version 1
  • ARXIV : 2011.09512

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Rodrigo Cofré, Cesar Maldonado, Bruno Cessac. Thermodynamic Formalism in Neuronal Dynamics and Spike Train Statistics. Entropy, MDPI, In press. ⟨hal-03015686⟩

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