[Mne_analysis] Regularization of the noise covariance matrix with tSSSed data

[Hari Bharadwaj]

Hi Ying,
   Also note that if you use the command line tools, you can explicitly set the rank to a reasonable number manually by using the --noiserank  input of mne_inverse_operator
or mne_do_inverse_operator. Of course, explicitly setting it can be dangerous if it does not correspond to the actual rank of the noise you have...

HTH,
Hari


Hari Bharadwaj
PhD Candidate, Biomedical Engineering,
Auditory Neuroscience Laboratory
Boston University, Boston, MA 02215

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

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

> On Jul 18, 2014, at 7:52 AM, Alexandre Gramfort <alexandre.gramfort at telecom-paristech.fr> wrote:
> 
> hi Ying,
> 
> try at first without regularizing. MNE should detect the rank
> automatically when whitening. It's however possible that tSSS makes
> rank estimation difficult due to slight head positions changes.
> 
> maybe Sheraz or Rey can share their insights too.
> 
> Alex
> 
> On Thu, Jul 17, 2014 at 6:43 PM, Ying Yang
> <evergreenlifeyangying at gmail.com> wrote:
>> Hi MNE experts,
>> 
>> I am wondering whether it is common to regularize the noise covariance
>> matrix for tSSSed data. Since tSSS may reduce the rank of the sensor data,
>> (in my case to 64),  the covariance matrix is singular too.  As a result,
>> the whitened forward gain matrix had a lot of zeros.
>> In this case, is it better to regularize the noise covariance matrix, or to
>> leave it intact such that the rank of noise matches the rank of  "signal"?
>> Thanks in advance!
>> 
>> Best,
>> Ying
>> 
>> 
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