Balanced networks in space

Wednesday, September 11, 2013 - 15:00
703 Thackeray Hall

Abstract or Additional Information

Networks of model neurons with balanced recurrent excitation and inhibition produce chaotic spiking activity that is irregular and asynchronous. We extend the analysis of balanced networks to include the known dependence of connection probability on the spatial separation between neurons. In the continuum limit we derive that stable, balanced firing rate solutions require that the spatial spread of external inputs be broader than that of recurrent excitation, which in turn must be broader than or equal to that of recurrent inhibition. For finite size networks we investigate the pattern forming dynamics arising when balanced conditions are not satisfied. The chaotic spatiotemporal dynamics of balanced networks offer new challenges in the statistical mechanics of complex systems.