Fig. 1: The adLIF neuron with membrane potential oscillation and spike-frequency adaptation.
From: Advancing spatio-temporal processing through adaptation in spiking neural networks
a Neurons in the brain have been classified into two excitability classes, integrators (class 1) and resonators (class 2). While resonators show membrane potential oscillations, integrators do not. b Membrane potential oscillation in response to an input pulse. The period P and decay r are sufficient to fully characterize the oscillating spike response. c Example of a neuron without (top) and with (bottom) spike frequency adaptation (SFA). Dotted arrow illustrates the feed-back of output spikes to the neuron membrane state in the adLIF model. d Adaptive LIF (adLIF) neurons (see Eq. (2)) differ in 2 features from vanilla LIF neurons: membrane potential oscillations and SFA. e Impulse response functions for different parameterizations of adLIF neurons. For a = 0 (green), no oscillations occur and the spike response reduces to leaky integration.
