[Mne_analysis] Localizing spontaneous activity: Best method / pipeline

[Leonardo Barbosa]

Hi Alex,

That is exactly what I was looking for! I grepped a little and found some
nice examples using it.

http://martinos.org/mne/stable/auto_examples/inverse/plot_compute_mne_inverse_epochs_in_label.html

Btw, can I make a suggestion? Change the name in the main menu from
"Gallery" to "Examples"!
I was mostly looking at Tutorials, imagining that Gallery was something
like figures and print-screens :)

Thank you!
Leonardo



2016-11-03 8:40 GMT-05:00 Alexandre Gramfort <alexandre.gramfort at telecom-
paristech.fr>:

> hi Leonardo,
>
> I will not comment on what's best but you can use all linear inverse
> solvers
> (beamformers, MNE/dSPM/sLORETA) on epochs or even raw data.
>
> Have a look at
>
> http://martinos.org/mne/stable/generated/mne.minimum_norm.
> apply_inverse_epochs.html#mne.minimum_norm.apply_inverse_epochs
> http://martinos.org/mne/stable/generated/mne.beamformer.
> dics_epochs.html#mne.beamformer.dics_epochs
> http://martinos.org/mne/stable/generated/mne.beamformer.
> lcmv_epochs.html#mne.beamformer.lcmv_epochs
>
> HTH
> Alex
>
>
> On Wed, Nov 2, 2016 at 11:48 PM, Leonardo Barbosa <lsbarbosa at gmail.com>
> wrote:
>
>> Dear MNE users!
>>
>> I've been trying to localize spontaneous activity for a week now, and
>> couldn't find much about this topic in the MNE list archives:
>>
>> https://mail.nmr.mgh.harvard.edu/mailman/swish/mne_analysis/
>> swish.cgi?query=spontaneous
>>
>> I think my main question for the moment would be: which method / pipeline
>> would be the most appropriate?
>>
>> Looking into the literature, it seems like DICS is most used, probably
>> because normally you are interested in some form of oscillatory component,
>> and DICS uses the cross-spectral density matrix
>>
>> http://martinos.org/mne/stable/auto_examples/inverse/plot_tf_dics.html
>> http://www.scholarpedia.org/article/Source_localization#Dyna
>> mic_imaging_of_coherent_sources_.28DICS.29
>>
>> Interestingly, tf_dics seems to be the only source localization / inverse
>> calculation that accept Epochs as parameter (although it calculates the csd
>> for each epoch, averages afterwards and return one source localization for
>> the average)
>> All the other methods expect Evoked data
>>
>> http://martinos.org/mne/stable/generated/mne.minimum_norm.ap
>> ply_inverse.html
>> http://martinos.org/mne/stable/generated/mne.inverse_sparse.
>> tf_mixed_norm.html
>>
>> etc
>>
>> So a more specific question would be:* How can I source localize each
>> epoch using for instance mne.inver_sparse, perform a PSD/TF tranformation
>> in*
>> *source space for each epoch, and then average the results? **Is there
>> some example in this sense?*
>>
>> There is an interesting post by Matti Hamalainen about that
>>
>> https://mail.nmr.mgh.harvard.edu/pipermail/mne_analysis/2009
>> -December/000336.html
>>
>> And taking into consideration the other posts and all the technical
>> aspects, I would prefer to apply the TF in source space and avoid
>> introducing temporal correlations in the signal if possible.
>>
>> Thank you in advance for any help!
>>
>> Leonardo
>>
>> ------------------------
>>
>> Leonardo S. Barbosa, PhD
>> Postdoctoral Research Scientist
>> University of Wisconsin, Madison
>> Center for Sleep and Consciousness Studies
>>
>>
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