Figure 1. Schematic of study and timescale inference technique.

(A) In this study, we infer neuronal timescales from intracranial field potential recordings, which reflect integrated synaptic and transmembrane current fluctuations over large neural populations (Buzsáki et al., 2012). Combining multiple open-access datasets (Table 1), we link timescales to known human anatomical hierarchy, dissect its cellular and physiological basis via transcriptomic analysis, and demonstrate its functional modulation during behavior and through aging. (B) Simulated time series and their (C) autocorrelation functions (ACFs), with increasing (longer) decay time constant, τ (which neuronal timescale is defined to be). (D) Example human electrocorticography (ECoG) power spectral density (PSD) showing the aperiodic component fit (red dashed), and the ‘knee frequency’ at which power drops off ($f_k$, red circle; insets: time series and ACF). (E) Estimation of timescale from PSDs of simulated time series in (B), where the knee frequency, $f_k$, is converted to timescale, τ, via the embedded equation (inset: correlation between ground truth and estimated timescale values).