In the context of multi-agent systems of binary interacting particles, a kinetic model for action potential dynamics on a neural network is proposed, accounting for heterogeneity in the neuron-to-neuron connections, as well as in the brain structure. Two levels of description are coupled: in a single area, pairwise neuron interactions for the exchange of membrane potential are statistically described; among different areas, a graph description of the brain network topology is included. Equilibria of the kinetic and macroscopic settings are determined and numerical simulations of the system dynamics are performed with the aim of studying the influence of the network heterogeneities on the membrane potential propagation and synchronization.

Action Potential Dynamics on Heterogeneous Neural Networks: From Kinetic to Macroscopic Equations / Bisi, Marzia; Conte, Martina; Groppi, Maria. - (2026), pp. 139-157. ( Final Conference of the COST Action MAT-DYN-NET Braga (Portugal) from 5 to 9 February 2024 from 5 to 9 February 2024) [10.1007/978-3-032-02326-1_4].

Action Potential Dynamics on Heterogeneous Neural Networks: From Kinetic to Macroscopic Equations

Conte, Martina;Groppi, Maria
2026

Abstract

In the context of multi-agent systems of binary interacting particles, a kinetic model for action potential dynamics on a neural network is proposed, accounting for heterogeneity in the neuron-to-neuron connections, as well as in the brain structure. Two levels of description are coupled: in a single area, pairwise neuron interactions for the exchange of membrane potential are statistically described; among different areas, a graph description of the brain network topology is included. Equilibria of the kinetic and macroscopic settings are determined and numerical simulations of the system dynamics are performed with the aim of studying the influence of the network heterogeneities on the membrane potential propagation and synchronization.
2026
9783032023254
9783032023261
File in questo prodotto:
File Dimensione Formato  
CleanRevision_Conte.pdf

embargo fino al 23/01/2027

Tipologia: 2. Post-print / Author's Accepted Manuscript
Licenza: Pubblico - Tutti i diritti riservati
Dimensione 1.28 MB
Formato Adobe PDF
1.28 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
BisiConteGroppi2026.pdf

accesso riservato

Tipologia: 2a Post-print versione editoriale / Version of Record
Licenza: Non Pubblico - Accesso privato/ristretto
Dimensione 835.42 kB
Formato Adobe PDF
835.42 kB Adobe PDF   Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/3007807