DYNAMICS OF POPULATIONS OF INTEGRATE-AND-FIRE NEURONS, PARTIAL SYNCHRONIZATION AND MEMORY

We study the dynamics of completely connected populations of refractor y integrate-and-fire neurons in the presence of noise. Solving the mas ter equation based on a mean-field approach, and by computer simulatio ns, we find sustained states of activity that correspond to fixed poin ts and show that for the same value of external input, the system has one or two attractors. The dynamic behavior of the population under th e influence of external input and noise manifests hysteresis effects t hat might have a functional role for memory. The temporal dynamics at higher temporal resolution, finer than the transmission delay times an d the refractory period, are characterized by synchronized activity of subpopulations. The global activity of the population shows aperiodic oscillations analogous to experimentally found field potentials.