meeg-cfin / sandbox

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document initial workflow for source localisation #11

Open cjayb opened 8 years ago

cjayb commented 8 years ago

Many source localisation methods exist, each with their parameter choices and idiosyncrasies. However, some basic steps are common to all methods (more or less?). I'd like to see a Wiki-page (with a suitably descriptive name so it will pop up when people use the search function...) with a simple walk-through. Each step could link to a more detailed description of

Things to leave out here (more advanced topics)

sarathykousik commented 8 years ago

_Coregistration_ MNE-C: Uses the ICP algorithm. Perfroms best in my view http://martinos.org/mne/dev/manual/sample_dataset.html#meg-mri-coordinate-system-alignment

MNE-Py: Better GUI. Seems issues were fixed recently. Perhaps mje knows better here (at the cost of repeating) http://www.slideshare.net/mne-python/mnepython-coregistration

Fieldtrip: Nothing great about their coreg tool. They suggest using the MEG manufacturer's tool anyway. http://www.fieldtriptoolbox.org/faq/how_to_coregister_an_anatomical_mri_with_the_gradiometer_or_electrode_positions

sarathykousik commented 8 years ago

Update on Fieldtrip & coreg - FT does have a not-so-good GUI for co-registration. Can be launched with the following code: Note: You need to first register as much as possible -> mri_ra. The let the ICP do a better job. It doesn't work that well in my experience. cfg = []; cfg.method = 'headshape'; cfg.coordsys = 'neuromag'; cfg.headshape.headshape = headshape; cfg.headshape.icp = 'yes'; cfg.headshape.interactive = 'yes'; mri_fine = ft_volumerealign(cfg, mri_ra);