AnalyzingData/MNE_overview - Meg Wiki

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Basics

[http://www.nmr.mgh.harvard.edu/martinos/userInfo/data/sofMNE.php MNE] data analysis uses information from structural MRI images, which have to be pre-processed using [http://surfer.nmr.mgh.harvard.edu/ Freesurfer]. You may want to start with the tutorial based on an example data set, as described in the [http://www.nmr.mgh.harvard.edu/meg/manuals/MNE-manual-2.6.pdf MNE manual] (chapter 12). Freesurfer is accompanied by extensive [http://surfer.nmr.mgh.harvard.edu/fswiki Freesurfer Wiki pages], containing a [http://surfer.nmr.mgh.harvard.edu/fswiki/FreeSurferBeginnersGuide Getting Started] and [http://surfer.nmr.mgh.harvard.edu/fswiki/UserContributions/FAQ FAQ] section. You will need some experience with Linux commands and scripting, which you may find on our [http://imaging.mrc-cbu.cam.ac.uk/meg/Beginners beginners' pages].

If you want to use the MNE Matlab toolbox on a regular basis, you should add the line

  • run /imaging/local/linux/mne_2.6.0/mne/matlab/toolbox/mne_setup_toolbox.m

to your startup.m file. If you run mne_setup_2.6.0 before starting Matlab, it will automatically add the paths to the MNE tools.

Overview of MNE Analysis Path

1) [http://imaging.mrc-cbu.cam.ac.uk/meg/AnalyzingData/MNE_MRI_preprocessing Pre-process your MRI Data Using Freesurfer]

2) [http://imaging.mrc-cbu.cam.ac.uk/meg/AnalyzingData/MNE_MRI_processing Create Source Space and Head Surfaces]

3) [http://imaging.mrc-cbu.cam.ac.uk/meg/AnalyzingData/MNE_ForwardSolution Compute the Forward Solution and BEM]

4) [http://imaging.mrc-cbu.cam.ac.uk/meg/AnalyzingData/MNE_CovarianceMatrix Compute the Noise Covariance Matrix]

5) [http://imaging.mrc-cbu.cam.ac.uk/meg/AnalyzingData/MNE_InverseOperator Compute the Inverse Operator]

6) [http://imaging.mrc-cbu.cam.ac.uk/meg/AnalyzingData/MNE_ComputeEstimates Compute the Source Estimates] (average cortical surface, grand-averaging)