[Mne_analysis] maxfilter for head movement compensation only
mainakjas at gmail.com
Tue May 7 09:57:23 EDT 2019
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On Tue, May 7, 2019 at 9:30 AM Evgenii Kalenkovich <e.kalenkovich at gmail.com>
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> Hi, dear Mainak.
> Let me make sure I understand correctly what you are proposing:
> 1. Run `maxwell_filter` without setting bad channels.
> 2. Run `autoreject` on the results of step 1 and identify bad channels.
> 3. Run `maxwell_filter` again supplying the list of channels
> identified in step 2.
> Does that make sense?
Umm ... sure you could try that but I suspect it may not work. I was
actually proposing to use SSP
for step 1. It's an alternative to SSS but in this situation, I think you
can use it here to complement SSS.
> I've just realized I have two further questions:
> 1. In this <https://github.com/autoreject/autoreject/issues/123>
> issue, @dengemann mentioned that `autoreject` does not identify flat
> channels. Do you think adding the following step would be appropriate?
> - 0. Run `mne.preprocessing.mark_flat` to identify flat channels.
> I've never tried this but it sounds reasonable to me.
> 1. Would you add temporal filtering before `autoreject`?
> You could highpass before to avoid marking too many segments as bad.
> On Tue, May 7, 2019 at 3:06 PM Mainak Jas <mainakjas at gmail.com> wrote:
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>> Hi Evgenii,
>> I remove bad channels/epochs at a later stage using the autoreject
>>>> One reproducible option would be to use autoreject or some other
>>>> automated routine to determine bad channels. MaxFilter even has an
>>>> `autobad` option you could try running before the head position estimation
>>>> step to get a list of bad channels. In principle you should be able to
>>>> combine head position estimation -headpos and automatic bad channel
>>>> detection -autobad, but in practice you can encounter bugs this way, so
>>>> it's safer to separate it into two steps.
>>> I did try running `autoreject` on the raw data cut into constant-width
>>> segments. Unfortunately, it results in half-to-all the channels being
>>> flagged as bad in most of the epochs. Also, the worst dozen or so channels
>>> were different both from the manually selected bad channels and the
>>> `autoreject`'s results with different settings (I've varied
>>> pre-`autoreject` linear filtering cutoffs, decimation factor, and segment
>> Just a note, the data before MaxFilter _does_ look bad, so it's not
>> surprising that these are all flagged as bad. Thus, I would say it's a
>> little hard to decouple SSS from the bad channel selection that SSS
>> requires. One option that might work for you is to apply first an SSP on a
>> copy of the data so you mimic the situation when you select bad channels.
>> And then apply autoreject on the SSP-ed data.
>>> I haven't tried MaxFilter's `-autobad` yet. Every person telling me how
>>> to use MaxFilter made sure to mention its unreliability so I've never
>>> considered it an option :-) I'll try and see whether the results are far
>>> from what manual inspection yields.
>>> Again, really appreciated your answer.
>>> Mne_analysis mailing list
>>> Mne_analysis at nmr.mgh.harvard.edu
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