NeuronGroup is the virtual base class of all neuron models within Auryn. It directly derives from SpikingGroup and implements important functionality which allows neurons to receive spikes. They are therefore the default target or destination type for Connection objects. Each non-virtual child of NeuronGroup has to implement the method evolve() which is called in every time step during simulations and is responsible to “evolve” the neural state variables.

• IFGroup: A conductance based integrate and fire model with absolute and relative refractory period. The model uses the reduced EPSP model introduced in Zenke et al. (2013) with slow and fast conductance components. It does not model the nonlinear voltage dependence of physiological NMDA channels, however.
• AIFGroup: Like IFGroup, but with additional spike triggered adaptation current.
• AIF2Group: Like AIFGroup, but two spike triggered adaptation current on different timescales which can be used to mimick power-law adaptation.
• TIFGroup: “Tim's Integrate and Fire” neuron model with absolute refractoriness. Simple conductance based integrate and fire model after Vogels and Abbott (2005).
• CubaIFGroup: Current based neuron model with absolute refractoriness as used in Vogels and Abbott (2005).
• AdExGroup: Adaptive integrate and fire neuron after Brette and Gerstner (2005).
• IzhikevichGroup: Implementation of quadratic adaptive Izhikevich neuron after Izhikevich (2003)
• IafPscDeltaGroup: Current-based integrate and fire neuron with delta current pulses. Similar to NEST implementation with the same name.
• IafPscExpGroup: Same as IafPscDeltaGroup, but with exponentially decaying synaptic current kernel.
• NaudGroup: Experimental two-compartment neuron model proposed by Richard Naud which can be used for burst multiplexing.
• SRM0Group: Implementation of a probabilistic SRM0 neuron after Gerstner et al. (2002, 2014).