= Tutorial 14: Noise covariance =
''Authors: Francois Tadel, Elizabeth Bock, John C Mosher, Sylvain Baillet''

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From continuous tutorials:

=== Noise covariance matrix ===
To estimate  the sources properly, we need an  estimation of the noise level for  each sensor. A good way to do this is  to compute the covariance matrix  of the concatenation of the baselines  from all the trials in both  conditions.

 * Select   at the same time the two groups of trials (right and left). To do  this:  hold the Control (or Cmd on Macs) key and click successively on  the Right and the Left  trial lists.
 * Right-click  on one of them and select: Noise covariance > Compute from  recordings. Set the baseline to '''[-104,-5] ms''',  to consider as noise everything that happens before the beginning of  the stimulation artifact. Leave the other options to the default values.  Click on Ok.
 * This  operation computes the noise covariance matrix based on the  baseline  of all the good trials (199 files). The result is stored in a new file  "Noise covariance" in the ''(Common files)'' folder.

{{http://neuroimage.usc.edu/brainstorm/Tutorials/TutRawAvg?action=AttachFile&do=get&target=noisecov.gif|noisecov.gif|class="attachment"}}

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