Thermodynamic Formalism in Neuronal Dynamics and Spike Train Statistics
Fecha
2020
Autores
Profesor Guía
Formato del documento
Articulo
ORCID Autor
Título de la revista
ISSN de la revista
Título del volumen
Editor
MDPI
ISBN
ISSN
item.page.issne
item.page.doiurl
Departamento o Escuela
Centro de Investigacion y Modelamiento de Fenomenos Aleatorios (CIMFAV)
Determinador
Recolector
Especie
Nota general
Resumen
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
Descripción
Lugar de Publicación
Auspiciador
Palabras clave
THERMODYNAMIC FORMALISM, NEURONAL NETWORKS DYNAMICS, MAXIMUM ENTROPY PRINCIPLE, FREE ENERGY AND PRESSURE, LINEAR RESPONSE, LARGE DEVIATIONS, ERGODIC THEORY