Figure 1.

(A) The learning window A(τ) used in the learning rule in Eq. (1) to model STDP. The window is the one introduced and motivated by Abarbanel et al. (2002), $A(\tau )=a_p{\text{e}}^{-\tau /T_p}-a_D{\text{e}}^{-\eta \tau /T_p}$ if τ > 0, $A(\tau )=a_p{\text{e}}^{\eta \tau /T_D}-a_D{\text{e}}^{\tau /T_D}$ if τ < 0, with the same parameters used in Abarbanel et al. (2002) to fit the experimental data of Bi and Poo (1998), a_p> = γ[1/T_p + η/T_D]⁻¹, a_D = γ[η/T_p + 1/T_D]⁻¹, with T_p = 10.2 ms, T_D = 28.6 ms, η = 4, γ = 42. Notably, this function satisfies the condition ${\displaystyle {\int }_{-\infty }^{\infty }}A(\tau )d\tau =0$, i.e. Ã(0) = 0. (B) The phase of the Fourier transform of A(τ) as a function of the frequency.