[Mne_analysis] Cortical labels power spectrum different approaches

[Peled, Noam]

Let me be more specific/clear:

I'm analyzing data from a patient with an ECOG. I want to compare the power-spectrum of the electrodes and the MEG cortical labels I've created around each electrode.

It seems that calculating the time series in the source space of long enough MEG epochs (~10s), split the electrodes file to same length epochs, and use

mne.time_frequency.psd_array_multitaper on both of them is the way to go, and also I know that both are in the same units (10*log10 for [dB]).
But I'm still a little bit confused by the different results I'm getting when using mne.minimum_norm.compute_source_psd_epochs instead.

Thanks,
Noam

________________________________
From: mne_analysis-bounces at nmr.mgh.harvard.edu <mne_analysis-bounces at nmr.mgh.harvard.edu> on behalf of Peled, Noam <NPELED at mgh.harvard.edu>
Sent: Wednesday, August 29, 2018 2:32:39 PM
To: mne_analysis at nmr.mgh.harvard.edu
Subject: [Mne_analysis] Cortical labels power spectrum different approaches


Hey all,

I'm calculating MEG cortical labels power spectrum (for resting state data) in two different ways. Can you help me understand the differences? The power spectrums are quite different (see attached).


1) Go through the source space time-series:

stcs = mne.minimum_norm.apply_inverse_epochs(epochs, ...)
labels_ts = mne.extract_label_time_course(stcs, labels, ...)
for label_ts:
  psds, freqs = mne.time_frequency.psd_array_welch(label_ts, ...)
  psds = 10 * np.log10(psds)



2) Compute the PSD from the epochs:


for label_ind, label in enumerate(labels):
  stcs = mne.minimum_norm.compute_source_psd_epochs(epochs, ...)
  for stc in stcs:
    psds = np.mean(stc.data, axis=0)



Thanks!

Noam

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