Dynamical phase separation on rhythmogenic neuronal networks.

Abstract

We explore the firing-rate model of excitatory neurons with dendritic adaptation (the Feldman-Del Negro model [J. L. Feldman and C. A. Del Negro, Nat. Rev. Neurosci. 7, 232 (2006)10.1038/nrn1871; D. J. Schwab et al., Phys. Rev. E 82, 051911 (2010)10.1103/PhysRevE.82.051911] interacting on a fixed, directed Erdős-Rényi network. This model is applied to the dynamics of the pre-Bötzinger complex, the mammalian central pattern generator with N∼10^{3} neurons, which produces a collective metronomic signal that times inspiration. In the all-to-all coupled variant of the model, there is spontaneous symmetry breaking in which some fraction of the neurons becomes stuck in a high-firing-rate state, while others become quiescent. This separation into firing and nonfiring clusters persists into more sparsely connected networks. In these sparser networks, the clustering is influenced by k cores of the underlying network. The model has a number of features of the dynamical phase diagram that violate the predictions of mean-field analysis. In particular, we observe in the simulated networks that stable oscillations do not persist in the high-sensitivity limit, in contradiction to the predictions of mean-field theory. Moreover, we observe that the oscillations in these sparse networks are remarkably robust in response to killing neurons, surviving until only approximately 20% of the network remains. This robustness is consistent with experiment.