Figure 2

Data-fitting to renewal equations with three different excitation time distributions f_E(t). (A) Empirical CDFs of two ISI data sets (same data sets as in Fig. 1A) in comparison to the theoretical CDF of f_ISI(t) (Eq. (8)) with exponentially-distributed excitation time f_E(t) (case (i)). (B) Differences between empirical and best-fit CDFs (as defined in Eq. (6)) for case (i) by quartiles for datasets (\(\ell \) < 1 in gray and \(\ell \) > 1 in black). (C) Empirical CDFs of two ISI data sets in comparison to theoretical CDF with gamma-exponential mixture excitation time (case (ii), same data sets as in (A)). (D) Best-fit values for 1 − p, the fraction events generated by the gamma distribution, against n, the gamma shape parameter. Dot size corresponds proportionally to the total difference between the empirical CDF and model CDF (larger dots correspond to larger differences). (E) Empirical CDFs of two ISI data sets in comparison to renewal CDF with two exponentials mixture excitation time (case (iii), same data sets as in (A)). (F) Box plots of best-fit rate parameters values λ_E1 and λ_E2 for datasets (\(\ell \) < 1 in gray and \(\ell \) > 1 in black). (G) Comparisons of total difference in empirical and theoretical CDFs (as defined in Eq. (6)) for for the three different models considered (case (i–iii)).