A numerical study of the time of extinction in a class of systems of spiking neurons

DOI10.1007/S10955-022-03060-9OpenAlexW2989201050WikidataQ116780602 ScholiaQ116780602MaRDI QIDQ2677654

Yanyan Li

Publication date: 5 January 2023

Published in: Journal of Statistical Physics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1911.02609

zbMATH Keywords

metastabilitynumerical simulationinteracting point processesstochastic model of spiking neurons

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20) Interacting random processes; statistical mechanics type models; percolation theory (60K35) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55)

Cites Work

• Unnamed Item
• Infinite systems of interacting chains with memory of variable length -- a stochastic model for biological neural nets
• Metastable behavior of stochastic dynamics: A pathwise approach
• Maximum likelihood analysis of spike trains of interacting nerve cells
• Maximum likelihood identification of neural point process systems
• Dynamics of sparsely connected networks of excitatory and inhibitory spiking neurons.
• Phase transition for infinite systems of spiking neurons
• A result of metastability for an infinite system of spiking neurons
• A system of interacting neurons with short term synaptic facilitation
• Lasso and probabilistic inequalities for multivariate point processes
• A Spike-Train Probability Model
• Microscopic approach of a time elapsed neural model
• A model for neural activity in the absence of external stimuli

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