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<p class=MsoNormal><font size=2 face=Arial><span style='font-size:10.0pt;
font-family:Arial'>I wonder whether it is better to use a single-mastoid
referenced data or average-mastoid referenced data when training </span></font><st1:City><st1:place><font
  size=2 face=Arial><span style='font-size:10.0pt;font-family:Arial'>ICA</span></font></st1:place></st1:City><font
size=2 face=Arial><span style='font-size:10.0pt;font-family:Arial'> on continuous
<span class=GramE>data?</span> When one mastoid is used for the reference,
another mastoid is typically left in the dataset – can this induce a bias
in the component configuration, especially over the back of the head? On the
other hand, when average of both mastoids is used, both channels have data in
them, which is, however, 100% correlated and smaller in magnitude than data on
other channels. Will this affect </span></font><st1:City><st1:place><font
  size=2 face=Arial><span style='font-size:10.0pt;font-family:Arial'>ICA</span></font></st1:place></st1:City><font
size=2 face=Arial><span style='font-size:10.0pt;font-family:Arial'> or not (since
the manipulation was linear)? If it will, should both mastoid channels be
deleted from the data?<o:p></o:p></span></font></p>

<p class=MsoNormal><font size=2 face=Arial><span style='font-size:10.0pt;
font-family:Arial'>Thank you—<o:p></o:p></span></font></p>

<p class=MsoNormal><font size=2 face=Arial><span style='font-size:10.0pt;
font-family:Arial'>Rita <span class=SpellE>Ceponiene</span> <span
style='mso-spacerun:yes'> </span><span
style='mso-spacerun:yes'> </span><span
style='mso-spacerun:yes'> </span><o:p></o:p></span></font></p>

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