pyrasa.irasa_mne.irasa_epochs#

pyrasa.irasa_mne.irasa_epochs(data: Epochs, band: tuple[float, float] = (1.0, 100.0), hset_info: tuple[float, float, float] = (1.05, 2.0, 0.05)) → IrasaEpoched[source]#

Separate aperiodic from periodic power spectra using the IRASA algorithm for Epochs data.

This function applies the Irregular Resampling Auto-Spectral Analysis (IRASA) algorithm as described by Wen & Liu (2016) to decompose the power spectrum of neurophysiological signals into aperiodic (fractal) and periodic (oscillatory) components. It is specifically designed for time-series data in mne.Epochs format, making it suitable for event-related EEG/MEG analyses.

Parameters:

  • data (mne.Epochs) – The time-series data used to extract aperiodic and periodic power spectra. This should be an instance of mne.Epochs.

  • band (tuple of (float, float), optional, default: (1.0, 100.0)) – A tuple specifying the lower and upper bounds of the frequency range (in Hz) used for extracting the aperiodic and periodic spectra.

  • hset_info (tuple of (float, float, float), optional, default: (1.05, 2.0, 0.05)) – Contains the range of up/downsampling factors used in the IRASA algorithm. This should be a tuple specifying the (min, max, step) values for the resampling.

Returns:

  • aperiodic (AperiodicEpochsSpectrum) – The aperiodic component of the data as an AperiodicEpochsSpectrum object.

  • periodic (PeriodicEpochsSpectrum) – The periodic component of the data as a PeriodicEpochsSpectrum object.

References

Wen, H., & Liu, Z. (2016). Separating Fractal and Oscillatory Components in the Power Spectrum of Neurophysiological Signal. Brain Topography, 29(1), 13–26. https://doi.org/10.1007/s10548-015-0448-0

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