[Mne_analysis] mne_compute_raw_inverse gave perfectly correlated source current estimates

[Kai Hwang]

Hi Matti and Alex,
Yes MEG-only solution worked. Now source estimates are no longer
perfectly correlated. Any idea what went wrong regarding including EEG
data into the inverse solution?

I used labels created by freesurfer's a2009 parcelation, I double
checked and they are correct.

Thanks!
Kai


On Thu, Feb 23, 2012 at 8:04 AM, Matti Hamalainen
<msh at nmr.mgh.harvard.edu> wrote:
>
> Hi Kai,
>
> In this kind of a case I suspect something is wrong with the noise covariance. What happens if you do an MEG-only solution, i.e., omit the --eeg option from mne_do_inverse_operator?
>
> - Matti
>
>
> On Feb 23, 2012, at 8:02 AM, Kai Hwang wrote:
>
>> Hi Alex, I changed --nave to 100 and still got perfect correlations.
>> Actually source estimates look identical between --nave 1 and --nave
>> 100.
>> Any other suggestions?
>> Thanks
>> Kai
>>
>> On Thu, Feb 23, 2012 at 2:44 AM, Alexandre Gramfort
>> <gramfort at nmr.mgh.harvard.edu> wrote:
>>> Hello Kai,
>>>
>>> a possible explanation is the "nave" used to set the regularization of
>>> the inverse problem.
>>>
>>> if you work with raw data, nave is 1 while with 100 epochs averaged
>>> it's 100 and the inverse
>>> solution is then far less regularized. A solution is to set the --nave
>>> option to a higher value in
>>> mne_compute_raw_inverse but you might amplify noise.
>>>
>>> hope this helps
>>>
>>> Alex
>>>
>>> On Thu, Feb 23, 2012 at 3:02 AM, Kai Hwang <kai.hwang at gmail.com> wrote:
>>>> Hello,
>>>>
>>>> I am trying to use mne_compute_raw_inverse to project single trial
>>>> epochs onto the surface. The command finishes without erros, but is
>>>> generating perfectly correlated source estimates from distant regions.
>>>> The scale and sign of current estimates differ, but the correlation is
>>>> either 1 or -1.
>>>> Below is the command:
>>>>
>>>> #do forward solution
>>>> mne_do_forward_solution --overwrite \
>>>> --meas ${s}_prep_ave.fif --subject ${s} --fwd ${s}_prep_ave_fwd.fif --meg --eeg
>>>>
>>>> #create inverse operator
>>>> mne_do_inverse_operator --fwd ${s}_prep_ave_fwd.fif --depth \
>>>> --loose 0.2 --meg --eeg --senscov ${s}_prep_cov.fif --subject ${s}
>>>>
>>>> #project raw data, for each label
>>>> mne_compute_raw_inverse --in ${s}_${rn}_sss_ds_raw.fif \
>>>> --inv ${s}_prep_ave_fwd.fif-meg-eeg-inv.fif \
>>>> --picknormalcomp \
>>>> --align_z \
>>>> --labeldir ./ALL-Labels \
>>>> --orignames \
>>>> --out ${s}-{rn}-label-source
>>>>
>>>> However, the same inverse operator worked fine with averaged evoked
>>>> data, results are reasonable when viewed in mne_analyze.
>>>> Any idea what could have gone wrong?
>>>>
>>>> Thanks!
>>>> Kai
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>



-- 
Kai Hwang, M.A.
Laboratory of Neurocognitive Development
Western Psychiatric Institute and Clinic
University of Pittsburgh Medical Center
http://www.pitt.edu/~kah124/