[Mne_analysis] equivalence of averaged single trial STCs and evoked STCs

[Hari Bharadwaj]

Also, it might be interesting to see what the default 'nave's are
apply_inverse() and apply_inverse_epochs() and what implications that
might have..


On Mon, March 10, 2014 3:26 pm, Denis-Alexander Engemann wrote:
> [reposted, attachment failure]
>
> Hi Dan,
>
> that was indeed a very good hint.
>
> I've updated the gist to do some more systematic comparisons between
> orientations and methods:
>
> https://gist.github.com/dengemann/9470121
>
> As to you clarification questions, the lines referred to in the legend  as
> 'single*' are related to averaging in source space.
>
> It seems using MNE and with a post-hoc normalization, e.g. using z-scores
> might be the way to go.
>>From my ad-hoc parameter experiment I cannot exclude the possibility,
>> that
> 'dSPM' and 'sLORETA' with 'normal' orientation might work as well.
> This would require a mean-flip method though which is not implemented in
> my
> script due to the manual extraction used.
> My extraction function, here, was `lambda x: np.abs(x).mean(0)`
>
> This needs more investigation + discussion
>
> Denis
>
>
> Images:
>
> https://www.dropbox.com/s/e4ykrm6xdh6ntio/fig-None-MNE.png
>
> https://www.dropbox.com/s/qwlt5ugxxo0owo2/fig-normal-MNE.png
>
> https://www.dropbox.com/s/mijmz9pvffgt5ms/fig-None-sLORETA.png
>
> https://www.dropbox.com/s/8dxf0czptuhyybs/fig-normal-sLORETA.png
>
> https://www.dropbox.com/s/hxcjla8x9euwzd3/fig-None-dSPM.png
>
> https://www.dropbox.com/s/e5pbr7iyday3za4/fig-normal-dSPM.png
>
>
>
>
> On Mon, Mar 10, 2014 at 7:13 PM, dgw <dgwakeman at gmail.com> wrote:
>
>> Hi Denis,
>>
>> Which line represents "averaging in source space" and which represents
>> "projecting evokeds"?
>>
>> Regardless. I think you are referring to why are the results different
>> when I average single trial data on the source space as opposed to
>> averaging that same data in sensor space and then source localizing?
>>
>> The first reason I can think of is that you are using the dSPM here and
>> I
>> believe that that can lead to some non-linearity between these results.
>> Do
>> you get the same problem with the L2?
>>
>>  HTH,
>> D
>>
>>
>> On Mon, Mar 10, 2014 at 1:56 PM, Denis-Alexander Engemann <
>> denis.engemann at gmail.com> wrote:
>>
>>> Hi folks,
>>>
>>> in one of my recent analyses I ran into some problems with regard to
>>> morphing and single trial
>>> label time series extraction which lead me to set up some comparisons:
>>>
>>> https://gist.github.com/dengemann/9470121
>>>
>>> (gist based on sample data, should run with a proper MNE-Python
>>> install)
>>>
>>> [image: Inline image 1]
>>>
>>> It turned out morphing was unproblematic, but,
>>> I'm wondering whether the differences between averaging in source space
>>> and
>>> projecting evokeds is expected, and if so, how it can be avoided?
>>>
>>> The background is that I'd like to be confident about the relating
>>> single
>>> trial analyses at the evoked level.
>>>
>>> Any thoughts?
>>>
>>> Cheers,
>>> Denis
>>>
>>>
>>>
>>>
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-- 
Hari Bharadwaj
PhD Candidate, Biomedical Engineering,
Boston University
677 Beacon St.,
Boston, MA 02215

Martinos Center for Biomedical Imaging,
Massachusetts General Hospital
149 Thirteenth Street,
Charlestown, MA 02129

hari at nmr.mgh.harvard.edu
Ph: 734-883-5954