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Published on: June 24, 2015
A Rate-Reduced Neuron Model for Complex Spiking Behavior
Koen Dijkstra1, Yuri A Kuznetsov2,3, Michel J A M van Putten4,5
1Department of Applied Mathematics, University of Twente, Enschede, The Netherlands. koen.dijkstra@utwente.nl.
Abstract:
We present a simple rate-reduced neuron model that captures a wide range of complex, biologically plausible, and physiologically relevant spiking behavior. This includes spike-frequency adaptation, postinhibitory rebound, phasic spiking and accommodation, first-spike latency, and inhibition-induced spiking. Furthermore, the model can mimic different neuronal filter properties. It can be used to extend existing neural field models, adding more biological realism and yielding a richer dynamical structure. The model is based on a slight variation of the Rulkov map.
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