Low-dimensional spike rate models derived from networks of adaptive integrate-and-fire neurons

Moritz Augustin, Josef Ladenbauer, Fabian Baumann & Klaus Obermayer
The spiking activity of single neurons can be well described by a nonlinear integrate-and-fire model that includes somatic adaptation. When exposed to fluctuating inputs sparsely coupled populations of these model neurons exhibit stochastic collective dynamics that can be effectively characterized using the Fokker-Planck equation. This approach, however, leads to a model with an infinite-dimensional state space and non-standard boundary conditions. Here we derive from that description four simple models for the spike rate dynamics in...
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