<div dir="ltr"><div><div>Thank you Denis,<br><br></div>Are there cases when it would be preferable to use the noise covariance?<br><br></div>Elena<br><div><div><div><div class="gmail_extra"><br><div class="gmail_quote">On 18 March 2015 at 16:04, Denis A. Engemann <span dir="ltr"><<a href="mailto:denis.engemann@gmail.com" target="_blank">denis.engemann@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="auto"><div>Hi Elena,</div><div><br></div><div>The defaults in ICA are good for what you want to do, channel-wise rescaling. See related examples on the webpage.</div><div><br></div><div><a href="http://martinos.org/mne/stable/auto_examples/preprocessing/plot_ica_from_raw.html" target="_blank">http://martinos.org/mne/stable/auto_examples/preprocessing/plot_ica_from_raw.html</a></div><div><br></div><div>Best,</div><div>Denis</div><div><div class="h5"><div><br>On 18 Mar 2015, at 15:46, Elena Orekhova <<a href="mailto:orekhova.elena.v@gmail.com" target="_blank">orekhova.elena.v@gmail.com</a>> wrote:<br><br></div><blockquote type="cite"><div><div dir="ltr"><div><div><div>Hello!<br><br>I would like to run ICA on Neuromag data (gradiometers + magnetometers).<br></div></div>As I understood, one can either use noise covariance matrix (from empty room data) or z-scoring to match the channel types. <br><br>Would the noise covariance be preferable?<br><br></div>Elena<br></div>
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