Mathematical neuroscience

Apparaît dans la collection : 2023 - T1B - WS1 - Structural learning by the brain

Why is it important to ground neuroscience in mathematics? What kind of mathematics are relevant in this scientific area where biology, perception; action and cognition are closely intermingled? What kind of relationships should be entertained with experimentalists and computationalists? In this lecture I will try to answer these questions through examples drawn from the analysis of the activity of large populations of neurons by mathematical methods from probability, statistics, and geometry.

Informations sur la vidéo

Date de captation 06/03/2023
Date de publication 06/03/2023
Institut IHP
Licence CC BY-NC-ND
Langue Anglais
Audience Doctorants
Réalisateur(s) Alexandre Duplessis, Marco Perez
Format MP4
Lieu IHP - Hermite Amphitheater

Données de citation

DOI 10.57987/IHP.2023.T1B.WS1.001
Citer cette vidéo Faugeras, Olivier (06/03/2023). Mathematical neuroscience. IHP. Audiovisual resource. DOI: 10.57987/IHP.2023.T1B.WS1.001
URL https://dx.doi.org/10.57987/IHP.2023.T1B.WS1.001

Domaine(s)

Neurosciences

Bibliographie

A. L. Hodgkin, A. F. Huxley / A quantitative description of membrane current and its application to conduction and excitation in nerve. Journal of Physiology, vol. 117 n°4, 1952. online
E. M. Izhikevich / Dynamical Systems in Neuroscience: The Geometry of Excitability And Bursting. 2007. online
John W. Evans / Nerve Axon Equations: 1 Linear Approximations. Indiana University Mathematics Journal, vol. 21 n°9, pp. 877–885, 1972. online