The spectrum of covariance matrices of randomly connected recurrent neuronal networks with linear dynamics.

ABSTRACT: A key question in theoretical neuroscience is the relation between the connectivity structure and the collective dynamics of a network of neurons. Here we study the connectivity-dynamics relation as reflected in the distribution of eigenvalues of the covariance matrix of the dynamic fluctuations of the neuronal activities, which is closely related to the network dynamics' Principal Component Analysis (PCA) and the associated effective dimensionality. We consider the spontaneous fluctuations around a steady state in a randomly connected recurrent network of stochastic neurons. An exact analytical expression for the covariance eigenvalue distribution in the large-network limit can be obtained using results from random matrices. The distribution has a finitely supported smooth bulk spectrum a

SUBMITTER: Hu Y 

PROVIDER: S-EPMC9345493 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature