[Mne_analysis] ERD/ERS on source space data

Thomas Hartmann thomas.hartmann at th-ht.de
Thu Oct 11 09:30:29 EDT 2018
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hi,

i faced a similar question some time ago. there is one thing to keep in 
mind when doing (time)frequency transforms on source data:

when data is projected to source space, it is projected to three 
components per source: one for each spatial dimension. these three 
components are then normally combined by taking the norm. this step 
includes squaring the data, so all samples that were negative are now 
positive. this is mostly ok when staying in the time-domain (although 
one must be aware of it, but it will not mess up anything). however, it 
essentially doubles the frequencies of all oscillations in your data, so 
it is highly problematic for (time)frequency transforms.

mne python provides a few ways to avoid this problem:

 1. use source_induced_power. this function calculates the TFR for all
    three components of every source and combines the power values
    afterwards.
 2. restrict the amount of spatial components per source to 1 when
    setting up the source model. i do not know if that is possible in
    mne python.
 3. restrict apply_inverse to return only one component.
    pick_ori='normal' would work well for EEG but not for MEG, though
    because it is mostly sensitive to the two tangential components.
 4. set pick_ori to 'vector' which should return all three spatial
    components per source, apply whatever algorithm(s) you need and
    combine them later yourself.

i hope, this is all correct. if not, please correct me!

cheers,
thomas


Am 11.10.18 um 15:04 schrieb Sheraz Khan, PhD:
> Yes, in addition, once you extract the source space data from the label,
> you can also use tfr_multitaper on the label time series.
>
> HTH
>
> Sheraz
>
>
>>          External Email - Use Caution
>>
>> You mean basically using source_induced_power instead o tfr_multitaper?
>>
>> Thanks for answering,
>> Karin
>>
>> Den tors 11 okt. 2018 kl 00:55 skrev Sheraz Khan, PhD <
>> sheraz at nmr.mgh.harvard.edu>:
>>
>>> Hi Karin,
>>>
>>> Yes, you need to pick few labels in the source space to estimate ERS/ESD
>>> on it.
>>>
>>> Please look at the following example:
>>>
>>>
>>> https://martinos.org/mne/stable/auto_examples/time_frequency/plot_source_label_time_frequency.html
>>>
>>> Thanks
>>>
>>> Sheraz
>>>
>>>
>>>>          External Email - Use Caution
>>>>
>>>> Hi!
>>>>
>>>> Is it possible to compute ERS/ERD maps based on source space instead
>>> of
>>>> sensor space?
>>>>
>>>> Best,
>>>> Karin
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>>>
>>> -------------------------
>>> Sheraz Khan, M.Eng, Ph.D.
>>> Instructor in Radiology
>>>
>>> Athinoula A. Martinos Center for Biomedical Imaging
>>> Massachusetts General Hospital
>>> Harvard Medical School
>>>
>>> McGovern Institute for Brain Research
>>> Massachusetts Institute of Technology
>>>
>>> Tel:   +1 617-643-5634
>>> Fax:   +1 617-948-5966
>>> Email: sheraz at nmr.mgh.harvard.edu
>>>         sheraz at mit.edu
>>> Web:   http://sheraz.mit.edu
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>
> -------------------------
> Sheraz Khan, M.Eng, Ph.D.
> Instructor in Radiology
>
> Athinoula A. Martinos Center for Biomedical Imaging
> Massachusetts General Hospital
> Harvard Medical School
>
> McGovern Institute for Brain Research
> Massachusetts Institute of Technology
>
> Tel:   +1 617-643-5634
> Fax:   +1 617-948-5966
> Email: sheraz at nmr.mgh.harvard.edu
>         sheraz at mit.edu
> Web:   http://sheraz.mit.edu
> _______________________________________________
> Mne_analysis mailing list
> Mne_analysis at nmr.mgh.harvard.edu
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-- 
Dr. Thomas Hartmann

Centre for Cognitive Neuroscience
FB Psychologie
Universität Salzburg
Hellbrunnerstraße 34/II
5020 Salzburg

Tel: +43 662 8044 5109
Email: thomas.hartmann at th-ht.de

"I am a brain, Watson. The rest of me is a mere appendix. " (Arthur Conan Doyle)

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