Extended Data Fig. 2: Algorithm performance on simulated data across a broader frequency range.
From: Parameterizing neural power spectra into periodic and aperiodic components
a-c, Power spectra were simulated across the frequency range (1–100 Hz), with two peaks, one in a low range, and one in a high range (see Methods), across five distinct noise levels (1000 spectra per noise level). a, Example power spectra with simulation parameters as aperiodic [offset, knee, exponent] and periodic [center frequency, power, bandwidth]. b, Absolute error of algorithmically identified peak center frequency, separated for the low (3–35 Hz) and high range (50–90 Hz) peaks. c, Absolute error of algorithmically identified aperiodic parameters, offset, knee, and exponent. All violin plots show full distributions, where small white dots represent median values and small box plots show median, first and third quartiles, and ranges. Note that the error axis is log-scaled in b and c.
