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Phase-slope index using spectral_connectivity_time instead of spectral_connectivity_epochs? #178
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This seems reasonable to me. IIUC, the original PR just didn't add @tsbinns any thoughts? |
I don't see any problems. With #163 merged mne-connectivity/mne_connectivity/spectral/time.py Lines 563 to 569 in 2af1398
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SG. Feel free to submit a PR @seqasim |
Sorry for the delay - created a PR here: #210 |
Also, I believe the same logic can be applied to dPLI? |
Seems like it. Perhaps that's worth a fresh PR to reduce individual diffs? |
Describe the problem
Currently, the function for computing phase-slope index is hard-coded to be computed over epochs to produce time-resolved PSI, and there's no option for computing the phase-slope index over time to produce PSI per epoch. This would be useful if you think the average directionality between two signals over the entire timecourse is informative. You could compute this by binning your trials into categories (i.e. good trials v. bad trials) and then computing PSI, but there's no way to compute PSI per epoch and relate it to continuous trial-level predictors. This should be possible unless I'm missing something
Describe your solution
Add a
_cohy
function tomne_connectivity.spectral.time
by removing the absolute value from_coh
Mimic conditional statements for
coh
forcohy
in_pairwise_con
and_parallel_con
Create a new function
phase_slope_index_time
that mimicsphase_slope_index
but utilizes our new computation ofcohy
using spectral_connectivity_time instead of spectral_connectivity_epochsDoes this sound reasonable or am I missing some obvious reason not to do this? If so, I'm happy to implement this and test and make a pull request.
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