Hi everyone,
I’m working on a time-frequency EEG analysis with MNE-Python with quite long epochs (9.6 seconds). I was wondering if baseline correction is recommended in this context, and if yes, at which point in the analysis is it best to do so: before or after the time-frequency transformation ?
This is what I know so far about baseline use:
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In evoked potentials (ERPs), baseline correction helps to eliminate variations in the initial baseline potential, ensure a stable reference and centers ERP variations around zero. It allow to enable deflections to be interpreted more easily.
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In time-frequency (TF) analysis, it seems that baselines are not always necessary. This is because oscillations are continuous, not strictly dependent on a resting potential, and spectral power measures relative amplitudes rather than absolute variations in potential. That said, a baseline can sometimes be used in TF to normalize spectral power or to control power variations between trials.
I understand that this can depend on the nature of the data, but given the length of my epochs, I’d like to know what the best practices are for reliable time-frequency analysis with long epochs.
Thanks for your feedback and advice!
Johan