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<p class=MsoNormal>Hello MNE users,<o:p></o:p></p>
<p class=MsoNormal>We are trying to compute single trial analysis at the source
level with MNE.<o:p></o:p></p>
<p class=MsoNormal>We understand that we do need an empty room recording from
the same day of the experimental recording to compute the noise covariance
matrix. Unfortunately for one set of data half of these recordings are missing.<o:p></o:p></p>
<p class=MsoNormal>My question is the following:<o:p></o:p></p>
<p class=MsoNormal>Is it better to use an empty room recording of a previous or
following day to our actual recording (taking into account that our setting
does not change from day to days)?<o:p></o:p></p>
<p class=MsoNormal>Or will it be better to compute an average noise covariance
matrix for the empty room recordings we do have and use this average for each
of our participants?<o:p></o:p></p>
<p class=MsoNormal>Moreover what kind of pre-processing this raw data should we
apply to?<o:p></o:p></p>
<p class=MsoNormal>I read in a previous thread that filtering from 1Hz-40Hz
could be a good idea but do we need to maxfilter this raw data before to
compute the noise covariance matrix?<o:p></o:p></p>
<p class=MsoNormal><o:p> </o:p></p>
<p class=MsoNormal>Thanks for your answer<o:p></o:p></p>
<p class=MsoNormal>Elisabeth<o:p></o:p></p>
<p class=MsoNormal><o:p> </o:p></p>
<p class=MsoNormal><o:p> </o:p></p>
<p class=MsoNormal>**********************<o:p></o:p></p>
<p class=MsoNormal>Dr Elisabeth Fonteneau<o:p></o:p></p>
<p class=MsoNormal>MRC Cognition and Brain Sciences Unit<o:p></o:p></p>
<p class=MsoNormal>15 Chaucer Road<o:p></o:p></p>
<p class=MsoNormal>Cambridge CB2 7EF<o:p></o:p></p>
<p class=MsoNormal>England<o:p></o:p></p>
<p class=MsoNormal>Tel: +44 (0)1223 355294 (extension 263)<o:p></o:p></p>
<p class=MsoNormal>Fax: +44 (0)1223 359062 <o:p></o:p></p>
<p class=MsoNormal><o:p> </o:p></p>
<p class=MsoNormal>Email: elisabeth.fonteneau@mrc-cbu.cam.ac.uk<o:p></o:p></p>
<p class=MsoNormal>Web:
http://www.mrc-cbu.cam.ac.uk/people/elisabeth.fonteneau/<o:p></o:p></p>
<p class=MsoNormal>**********************<o:p></o:p></p>
<p class=MsoNormal><o:p> </o:p></p>
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