Berlin 2024 – wissenschaftliches Programm
Bereiche | Tage | Auswahl | Suche | Aktualisierungen | Downloads | Hilfe
BP: Fachverband Biologische Physik
BP 13: Statistical Physics of Biological Systems I (joint session DY/BP)
BP 13.8: Vortrag
Dienstag, 19. März 2024, 11:45–12:00, BH-N 334
Mesoscopic dynamics of spiking neuron population with quenched randomness — •Nils Erik Greven1,2, Jonas Ranft3, and Tilo Schwalger1,2 — 1TU Berlin — 2BCCN Berlin — 3IBENS, Ecole Normale Supérieure & CNRS
To understand the neural mechanisms underlying the response and variability dynamics of neuronal populations in the brain, simple mean-field models at the mesoscopic scale are required that faithfully describe the fluctuations of population activities and recurrent synaptic inputs in network of spiking neurons. We derive a nonlinear stochastic mean-field model for a network of spiking Poisson neurons with random connectivity. The quenched disorder of the connectivity is treated by an annealing approximation leading to a simpler fully connected network with additional noise in the neurons. This annealed network enables a reduction to a mesoscopic model as a two-dimensional closed system of coupled Langevin equations for the mean and variance of the neuronal membrane potentials. Compared to microscopic simulations, the mesoscopic model well describes the fluctuations and nonlinearities of finite-size neuronal populations and outperforms previous mesoscopic models that neglected the recurrent noise effect caused by quenched disorder. This effect can be analytically understood as a softening of the effective nonlinearity. The mesoscopic theory also shows that, in the presence of synaptic transmission delays, quenched disorder can stabilize the asynchronous state. Furthermore, our theory correctly predicts the effect of connection probability and stimulus strength on the variance of the population firing rate.
Keywords: neural population dynamics; random networks; spiking neurons; stochastic mean field models; mesoscopic fluctuations