I’m attempting to estimate frontoparietal theta phase coherence using an EEG dataset. I would like to estimate coherence between a set of frontal (e.g., AFz, Fz, FPz, AF3, and AF4) and parietal (e.g., PO8, P8, and P10) electrodes. I’m unsure what the best approach to achieve this is:
- Average the time domain signal over the electrode sets first. Then estimate coherence between the averaged ‘frontal’ and ‘parietal’ region.
- Extract the phase angle time series for each electrode separately, average phase angles over the electrode sets, and then estimate phase coherence.
- Compute coherence between all pairs of electrodes and then average coherence over channels.
Just to add, I have already applied a Laplacian filter to the data.
Any thoughts? TIA!