tf_mixed_norm applied to epochs?

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1

Hello,

    Is there a way to produce individual epoch-level output from the recent tf_mixed_norm localization? I need epochs to pass to spectral estimation and further processing. Thanks,

Per A. Lysne

University of New Mexico
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2

hi Per,

    Is there a way to produce individual epoch-level output from the recent
tf_mixed_norm localization? I need epochs to pass to spectral estimation and
further processing. Thanks,

we've been working on this feature with Daniel Strohmeier for some time
now but it's not ready yet.

If you apply a non-linear inverse method on just one epoch it does not work
so you need to do something smarter to combine all epochs.

Alex

3

Would it be possible to separate the TF-MxNE inverse operator from the data to which it is applied? This would be similar to the L-1 MNE inverse, where "make_inverse_operator" is separate from "apply_inverse"? In which case the localization could be performed on average evoked data, and then the solution could be applied to epochs?

Thanks again,

-Per

P.S. tf_mixed_norm appears to discard the sign of the timecourses? I.e. they are always non-negative? Can the sign be retained?

4

Would it be possible to separate the TF-MxNE inverse operator from the data to which it is applied? This would be similar to the L-1 MNE inverse, where "make_inverse_operator" is separate from "apply_inverse"? In which case the localization could be performed on average evoked data, and then the solution could be applied to epochs?

well we could do this, which would amount to run a least square on the activeset
(active sources + TF coefs) but the TF-MxNE solver like any non L2 solver does
not work this way. The solution is a non-linear operation computed on the
data at hand. How skilled are you with Python / MNE-Python to experiment
with this?

P.S. tf_mixed_norm appears to discard the sign of the timecourses? I.e. they are always non-negative? Can the sign be retained?

we should add a pick_ori parameter to be able to keep the normal component only.
Otherwise you can keep the sign if you disable the loose parameter or
use a fixed
orientation constraint.

Alex