I am working with intracranial EEG data for which I am using the mne-connectivity package to do amplitude envelope correlation (AEC) in order to estimate functional connectivity between channels. (I am not using orthogonalized AEC because the channels are directly measuring intracranial local field potentials.)
The envelope correlation function,
mne_connectivity.envelope_correlation, returns a connectivity matrix representing a single correlation value per channel pair, measured across the specified time window, bandwidth, and epochs.
Instead, I would like to generate AEC values for every time point and frequency, measured across epochs, so that I can plot a time-frequency spectrogram of AEC values for every channel pair. Any ideas on how can I do this?
Hi Dan, thank you for the suggestion!
I looked at
mne_connectivity.spectral_connectivity, and all of the supported connectivity measures listed in the documentation were based on phase synchronization (coherence, PLV, PLI, etc.). There weren’t any metrics based on amplitude/power envelope correlation.
But I could be missing something?
ah, sorry, you’re right. I didn’t realize that.
A related question:
I’m not orthogonalizing the AEC values given that my data is from intracranial EEG recordings (I use the
orthogonalization = False option for
My understanding is that the orthogonalization procedure is used only to account for confounding when reconstructing signals in source space from sensor space scalp EEG data.
Am I correct in my choice? I can start a new topic if this question should be moved elsewhere.