I've been working recently with the Python toolbox trying to examine
higher-frequency activity in an auditory paradigm. The PLV seems OK, but
there are strange things happening at the edges of the induced power matrix
which I think are obscuring whatever power is induced by the stimulus.
When I process the sample dataset with the exact same script, I don't see
such edge effects. Does anyone have any ideas about why this is
happening?
A related general question: Is the evoked field subtracted from the
individual epochs prior to computation?
I've been working recently with the Python toolbox trying to examine
higher-frequency activity in an auditory paradigm. The PLV seems OK, but
there are strange things happening at the edges of the induced power matrix
which I think are obscuring whatever power is induced by the stimulus. When
I process the sample dataset with the exact same script, I don't see such
edge effects. Does anyone have any ideas about why this is happening?
what you see is normal as no correction is done about edge artifact. The
way I do it is by clipping the TFR maps at the beginning and at the end.
Also baseline should not include the coefficients with artifact.
A related general question: Is the evoked field subtracted from the
individual epochs prior to computation?
no. Separating evoked from induced by subtracting the mean is usually
not enough.
I agree that the term "induced" can therefore be misleading as
currently described.
Feel free so send us some suggestions and code to improve this part of
the mne-python
code.