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iSTTC: A robust method for accurate estimation of intrinsic neural timescales from single-unit recordings

Fig 4

iSTTC provides better IT estimates from epoched spiking activity.

(A) Schematic illustration of the generation of epoched data based on randomly sampled unsegmented spike trains. Dice icon from svgrepo.com. (B) Hexbin plot displaying the difference in REE between iSTTC and PearsonR as a function of firing rate and excitation strength (left), and IT and excitation strength (right) (n = single units, 40 trials x 1000 ms each). Color codes for the median REE difference in each bin, with blue indicating lower error for iSTTC. (C) Line plot displaying predicted REE values for iSTTC and PearsonR as a function of firing rate (left), excitation strength (middle), and IT (right) (n = single units, 40 trials x 1000 ms each). Shaded areas represent 95% confidence intervals. Y-axes are plotted on a scale. In (B) and (C), PearsonR parameters were: bin size = 50 ms, number of lags = 20; iSTTC parameters were: lag shift = 50 ms, dt = 25 ms, number of lags = 20. In (B), asterisks indicate a significant effect of the method. In (C), asterisks indicate a significant effect of an interaction between method and firing rate (left), method and excitation strength (middle), and method and IT (right). * , ** , *** . Generalized linear model with interactions (B), (C).

doi: https://doi.org/10.1371/journal.pcbi.1013385.g004