[Mne_analysis] Denoise MEG from ref sensor using TSPCA

Teon Brooks teon.brooks at gmail.com
Wed Nov 25 17:46:33 EST 2015
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Hey JR,

I have an open issue <https://github.com/mne-tools/mne-python/issues/2112>
on github along these lines. I know that there was a MEG denoise repo
<https://github.com/pealco/python-meg-denoise> that has the tsPCA approach
along with DSS and SNS. It was done by a graduate student at UMD.
For the KIT system, the compensation isn't done online. It seems like the
exact use case you are mentioning, but I haven't had the time to evaluate
where it was properly implemented. I would be interested in helping where I
can but I wouldn't be able to lead that integration.

I would be interested in the comparison of an SSS approach and the tsPCA
approach.

HTH,

-teon

On Wed, Nov 25, 2015 at 5:13 PM, Denis-Alexander Engemann <
denis.engemann at gmail.com> wrote:

> Hi JR,
>
> we have an SSS implementation in Python, but it's still under validation,
> right Eric?
> How is the data quality on your KIT system? Do you see an urgent need to
> decompose your signals / regress out extrnal influences? AFAIK on a 4D
> system the reference sesnors are already used during acquisition for online
> compensation.
>
> -D
>
> On Wed, Nov 25, 2015 at 11:01 PM, JR KING <jeanremi.king at gmail.com> wrote:
>
>> Hi all,
>>
>> I am currently starting to use a KIT system, in which there's a
>> reference sensor a bit further away from the head than the other
>> sensors, and which is used to specifically record environmental noise.
>>
>> Most people in my lab use a 'time-shit PCA' to denoise the signals.
>> They use a Matlab library for this:
>> http://www.isr.umd.edu/Labs/CSSL/simonlab/Denoising.html
>>
>> I was wondering whether some of you had tried this method, and
>> compared it to other denoising approaches such as SSS? If so, is there
>> a python implementation?
>>
>> Thanks!
>>
>> JR
>>
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