2022 - T1 - WS2 - Mathematical modeling and statistical analysis in neuroscience

Collection 2022 - T1 - WS2 - Mathematical modeling and statistical analysis in neuroscience

Organizer(s) Ditlevsen, Susanne ; Faugeras, Olivier ; Galves, Antonio ; Reynaud-Bouret, Patricia ; Salort, Delphine ; Shinomoto, Shigeru

Date(s) 31/01/2022 - 04/02/2022

linked URL https://indico.math.cnrs.fr/event/6532/

00:00:00 / 00:00:00

26 30

Towards understanding the time periodic solutions in a kinetic model for neuron networks

By Zhennan Zhou

In this talk, we are concerned with a kinetic model for neuron networks, where individual neurons are characterized by their voltage and conductance. The dynamics of the voltage is influenced by the conductance and when the voltage is reaching a threshold, it is immediately reset to a lower value. By exploring a series of simplified models, we aim to identify the cause of the emergence of time-periodic solutions in such Fokker-Planck equations.

Information about the video

Date of recording 04/02/2022
Date of publication 04/02/2022
Institution IHP
Language English
Audience Researchers
Director(s) Mandarine Audiovisuel
Format MP4
Venue IHP - Hermite Amphitheater

Citation data

DOI 10.57987/IHP.2022.T1.WS2.026
Cite this video Zhou, Zhennan (04/02/2022). Towards understanding the time periodic solutions in a kinetic model for neuron networks. IHP. Audiovisual resource. DOI: 10.57987/IHP.2022.T1.WS2.026
URL https://dx.doi.org/10.57987/IHP.2022.T1.WS2.026

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