[Mne_analysis] mne_compute_raw_inverse gave perfectly correlated source current estimates

[Hwang, Kai]

Hi Matti,
Bad channels were previously marked using mne_mark_bad_channels. I went through the raw data again by turning off EEG reference projection, and added a couple more to the bad list. I also added "eegReject 40e-6" to the covariance file. That worked, now source estimates are no longer perfectly correlated.
Thanks!
Kai



On Feb 23, 2012, at 9:40 AM, Matti Hamalainen wrote:

> 
> On Feb 23, 2012, at 9:20 AM, Kai Hwang wrote:
> 
>> 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.
> 
> Are some of the EEG channels dysfunctional and not marked bad? Have you checked the EEG data by switching the average EEG reference off in mne_browse_raw?
> 
> - Matti
> 
> 
>> 
>> 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/
>> 
>> 
> 
> 

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