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Thermodynamic Formalism in Neuronal Dynamics and Spike Train Statistics

dc.contributor.authorCofré, Rodrigo
dc.contributor.authorMaldonado Ahumada, César Octavio
dc.contributor.authorCessac, Bruno
dc.identifier.citationCofré, R.; Maldonado, C.; Cessac, B. Thermodynamic Formalism in Neuronal Dynamics and Spike Train Statistics. Entropy 2020, 22, 1330.
dc.description.abstract"The Thermodynamic Formalism provides a rigorous mathematical framework for studying quantitative and qualitative aspects of dynamical systems. At its core, there is a variational principle that corresponds, 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, in order 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."
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional
dc.subjectThermodynamic Formalism
dc.subjectNeuronal networks dynamics
dc.subjectMaximum entropy principle
dc.subjectFree energy and pressure
dc.subjectLinear response
dc.subjectLarge deviations
dc.subjectErgodic theory
dc.titleThermodynamic Formalism in Neuronal Dynamics and Spike Train Statistics
dc.rights.accessAcceso Abierto

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Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 Internacional