THREE GENERIC MECHANISMS FOR SYNCHRONY OF NEURAL ACTIVITY AND THE STABILITY OF PERSISTENT STATES IN LARGE NEURONAL NETWORKS.

D. HANSEL; G. MATO

New Orleans, USA

Conferencia; Society for Neuroscience Meeting; 2000

Society for Neuroscience

We study how synchrony emerges in highly connected heterogeneous networks consisting of two interacting populations of neurons, one excitatory (E) and one inhibitory (I). We find that three generic mechanisms exist: 1) Synchrony of spikes through inhibition in the I population. 2) Synchrony of spikes through the mutual interactions between the two populations. 3) Synchrony of network bursts through recurrent excitation. We show that these mechanisms differ by the role of excitatory and inhibitory interactions and by their robustness to heterogeneities and noise. We have computed analytically the regions in parameter space where the different mechanisms occur for integrate-and-fire and similar models. For conductance-based neuronal models, we have relied on numerical simulations. The cellular and synaptic properties underlying stable persistent state (PS) of activity in neuronal circuits have been debated recently in the context of models of working memories. Using our analytical approach we have derived conditions for the stability of PS. We have shown that PS with level of activity of the order of 5-20 Hz can be stable in a broad range of parameters of a two population network of neurons interacting with AMPA and GABA synapses, provided the level of heterogeneities in the intrinsic properties of neurons is sufficient. This is in contrast with previous theoretical studies which have suggested that saturating NMDA synapses are required to stabilize cortical persistent activity with physiologically realistic firing rates.