Hi, I'm currently trying to estimate spectral coherence between two signals recorded from the same channel in two different conditions. This is fine when applying this to an individual subject, however, I am uncertain of how to quantify and compare this at the group level (six subjects, two conditions).
Any help would be greatly appreciated.
Many thanks
Hi Nik,
In EEG analysis usually coherence is calculated between pairs of channels recorded from the same subject, such that the time courses of both channels in each epoch refer to the same time points. I don't think resting EEG would be very coherent when calculating within a subject when using two time courses / epoch sets that are recorded at different times. Perhaps stimulus-locked EEG would be coherent, but usually we would use a phase-locking index (PLI) in that scenario. Anyway, be sure to look at many frequency bands of EEG so you have some noise floor for your measure (i.e. see Figure 7 in the attached book chapter).
If you're going to instead calculate coherence between two electrodes, and then compare coherence measures across subjects, then you would have to take into account individual variation in head volume conduction properties. Calculating a coherence-noise floor for each subject by looking across many frequency bands may help you.
Chapter Electroencephalography (EEG): neurophysics, experimental met...
Ok, thanks. Perhaps I'm going about this the wrong way. I'm not trying to establish connectivity, infact I'm seeking to compare the spectral content of two signals recorded at the same location. Is there a more relevant approach that I could use instead, or would I be better taking the PSD and comparing the power and peak frequencies within the delta to gamma bands?
There is a paper talks exactly about this.
http://www-users.med.cornell.edu/~jdvicto/pdfs/bopusf06.pdf
Sure there should be a toolbox somewhere were it is already implemented.
Thanks Luis, I'll give this a read as well and hopefully refine my ideas.
Nik,
It seems like you want to standardize each subject's FFT or wavelet spectra by some baseline amplitude (or standardize by amplitude of surrounding frequency bands) to account for volume conduction differences and then compare across subjects. Spectral estimates within the same subject could be directly compared (if you have enough samples per condition) or the standardized spectra could be compared.
You may also want to sum across power measures in certain frequency bands to calculate power in a certain range (e.g. alpha 8-12 Hz) that encompasses each subject's peak. Subjects have individual variation in the frequency location of certain bands (e.g. one subject will have a peak resting alpha peak at 8 Hz while another subject will have a peak resting alpha peak at 10 Hz).
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