Supplemental Materials - Detailed model specification and model fits

The model consists of units that represent the firing rate V of entire neural populations. We assume the inputs to a population have Gaussian white noise added to them (Wiener process W ), which models the input variability introduced by stochastic spike-generation in the input populations, and is weighted by a factor c. V (t) can thus be interpreted as the dynamic rate parameter of a nonhomogeneous Poisson process; it is defined as follows, with the subscript i denoting ‘units’ representing distinct populations, and wij denoting entries of the connection matrix linking units into a network: