<div dir="ltr"><div><div>Hi Qiong,<br><br></div>`mne_map_data` uses Minimum Norm
Estimate. You project your data onto a sphere and project it back to the
new sensor locations. Actually, you should be able to find the Mathematical
details in Matti's 1994 paper: <a href="http://link.springer.com/article/10.1007%2FBF02512476?LI=true" target="_blank">http://link.springer.com/artic<wbr>le/10.1007%2FBF02512476?LI=<wbr>true</a>.<br><br></div>Mainak<div class="gmail_extra"><br><div class="gmail_quote">On Mon, May 1, 2017 at 5:32 PM, <span dir="ltr"><<a href="mailto:qiongz@andrew.cmu.edu" target="_blank">qiongz@andrew.cmu.edu</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr">Hi Alex,<div><br></div><div>Thanks so much for the information. I really appreciate it. I have looked into papers during that period of time by matti Hämäläinen, with the most relevant material in <a href="https://mycourses.aalto.fi/pluginfile.php/123749/mod_resource/content/1/2002-Hämäläinen-BrainMappingMethods.pdf" target="_blank">this chapter</a> p237 last paragraph in section 3 providing some understanding of the problem: </div><div><br></div><div><font face="arial, helvetica, sans-serif">"The continuous records of the head movements can then be utilized in different correction
methods. If the signal-to-noise ratio is so good that unaveraged signals can be modeled, one can
simply use a different coordinate transformation between the anatomical and device coordinate
frames at each time instant. The situation is more complicated if signals are averaged or if
continuous data segments containing signals from supposedly identical source distributions are
compared. Uutela et al. (2001) have recently explored several alternative computational
approaches applicable to signal averaging and source modelling in situations with significant
head movements during the data acquisition.</font></div>
<div><font face="arial, helvetica, sans-serif"> "</font></div><div><font face="arial, helvetica, sans-serif"><br></font></div><div><font face="arial, helvetica, sans-serif">As the name 'mne_map_data' s</font>uggests the use of simple transformation and is often applied by sessions/blocks, correct me if I'm wrong, it seems to implement different transformations between the anatomical and device coordinate frames using data averaged within those sessions/blocks. As a result, the sensor data is transformed as if they are recorded from the same anatomical positions across these sessions/blocks. </div><div><br></div><div><br></div><div>Best,</div><div>Qiong</div><div><div class="m_-7425607641854867411h5"><div><br></div><div class="gmail_extra"><br><div class="gmail_quote">On Mon, May 1, 2017 at 8:53 AM, Alexandre Gramfort <span dir="ltr"><<a href="mailto:alexandre.gramfort@telecom-paristech.fr" target="_blank">alexandre.gramfort@telecom-pa<wbr>ristech.fr</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr">hi,<div><br></div><div>mne_map_data is based on Matti's paper from the early 90's AFAIK.</div><div><br></div><div>for some reason mne_map_data seems to be absent from the MNE website</div><div>and even from the original MNE manual...</div><div><br></div><div>Alex</div><div><br></div></div><div class="gmail_extra"><br><div class="gmail_quote"><div><div class="m_-7425607641854867411m_-3515456839452967622h5">On Fri, Apr 28, 2017 at 7:43 PM, <span dir="ltr"><<a href="mailto:qiongz@andrew.cmu.edu" target="_blank">qiongz@andrew.cmu.edu</a>></span> wrote:<br></div></div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div><div class="m_-7425607641854867411m_-3515456839452967622h5"><div dir="ltr">Dear MNE users,<div><br></div><div>I am trying to understand the difference between using MaxFilter (SSS based) and using 'mne_map_data' to correct for head movement. Does anyone know what algorithm is implemented for 'mne_map_data'? </div><div><br></div><div>Thanks in advance for any help!</div><div><br></div><div>Best,</div><div><br></div><div>Qiong</div><div><br></div><div><div>------------------------------<wbr>---------------------------</div><div><br></div><div>Qiong Zhang</div><div><br></div><div>PhD Student</div><div>Machine Learning & Neural Computation </div><div>Carnegie Mellon University </div></div></div>
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