Probabilistic spiking neuronal nets - Neuromathematics for the computer era

Antonio Galves (1) , Eva Löcherbach (2) , Christophe Pouzat (3)

1 USP - Universidade de São Paulo = University of São Paulo
2 SAMM - Statistique, Analyse et Modélisation Multidisciplinaire (SAmos-Marin Mersenne)
3 IRMA - Institut de Recherche Mathématique Avancée

This book presents and studies a class of stochastic models for biological neural nets. A biological neural net is a system with a huge number of interacting components, the neurons. The activity of each neuron is represented by a point process, namely, the successive times at which the neurons emit an action potential, also called a spike. It is generally considered that the spiking activity is the way the system encodes and transmits information.

Mots clés: PDMP; spike trains statistics; System of spiking neurons; processes with a memory of variable length

Domaines: Applications [stat.AP]; Probabilités [math.PR]; Neurosciences [q-bio.NC]

Antonio Galves, Eva Löcherbach, Christophe Pouzat. Probabilistic spiking neuronal nets - Neuromathematics for the computer era. 2021. ⟨hal-03196369⟩