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Neuronal Spike Timing Adaptation Described with a Fractional Leaky Integrate-and-Fire Model

Figure 1

Comparison between the classical and fractional leaky integrate-and-fire models.

(A) Schematic circuit diagrams for the classical (left) and fractional order (right) leaky integrate-and-fire models. (B) Sub-threshold response in the classical (left) and fractional models (right). Both stimulated with nA. (C) The sub-threshold voltage response converges to a power-law function when decreases. (D) While the classical model (left) generates regular spiking to a constant input, the fractional model (right) shows first spike latency and spike adaptation. Both models stimulated with nA. (E) The first-spike latency produced by the fractional model becomes longer when is smaller. (F) The inter-spike interval histogram as a function of . The histogram shows power-law distribution as . (G) The inter-spike intervals decrease over time as a function of . The color key in C applies to F and G.

Figure 1

doi: https://doi.org/10.1371/journal.pcbi.1003526.g001