26 citations · 35 across the 7 of their papers we have counts for
7 papers
Mathematical studies of the dynamics of finite-size binary neural networks: A review of recent progress
Diego Fasoli, Stefano Panzeri
Traditional mathematical approaches to studying analytically the dynamics of neural networks rely on the mean-field approximation, which is rigorously applicable only to networks o…
Stationary-State Statistics of a Binary Neural Network Model with Quenched Disorder
Diego Fasoli, Stefano Panzeri
We study the statistical properties of the stationary firing-rate states of a neural network model with quenched disorder. The model has arbitrary size, discrete-time evolution equ…
Optimized brute-force algorithms for the bifurcation analysis of a spin-glass-like neural network model
Diego Fasoli, Stefano Panzeri
Bifurcation theory is a powerful tool for studying how the dynamics of a neural network model depends on its underlying neurophysiological parameters. However, bifurcation theory h…
Pattern Storage, Bifurcations and Higher-Order Correlation Structure of an Exactly Solvable Asymmetric Neural Network Model
Diego Fasoli, Anna Cattani, Stefano Panzeri
Exactly solvable neural network models with asymmetric weights are rare, and exact solutions are available only in some mean-field approaches. In this article we find exact analyti…
From Local Chaos to Critical Slowing Down: A Theory of the Functional Connectivity of Small Neural Circuits
Diego Fasoli, Anna Cattani, Stefano Panzeri
Functional connectivity is a fundamental property of neural networks that quantifies the segregation and integration of information between cortical areas. Due to mathematical comp…
The complexity of dynamics in small neural circuits
Diego Fasoli, Anna Cattani, Stefano Panzeri
Mean-field theory is a powerful tool for studying large neural networks. However, when the system is composed of a few neurons, macroscopic differences between the mean-field appro…
Mean Field description of and propagation of chaos in recurrent multipopulation networks of Hodgkin-Huxley and Fitzhugh-Nagumo neurons
Javier Baladron, Diego Fasoli, Olivier Faugeras +1
We derive the mean-field equations arising as the limit of a network of interacting spiking neurons, as the number of neurons goes to infinity. The neurons belong to a fixed number…