A Rate-Reduced Neuron Model for Complex Spiking Behavior

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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.
Original languageEnglish
Article number13
Number of pages18
JournalJournal of mathematical neuroscience
Publication statusPublished - 11 Dec 2017


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