EEG/MEG source imaging in the absence of subject's brain MRI scan: Perspective on co-registration and MRI selection approach

摘要

EEG/MEG source localization requires a subject's brain MRI to compute the sourcemodeland headmodel. As part of this computation, co-registration of the digitizedhead information and brain MRI scan is the essential step. However, in theabsence of a brain MRI scan, an approximated sourcemodel and headmodel canbe computed from the subject's digitized head information and brain MRI scansfrom other subjects. In the present work, we compared the fiducial (FID)- anditerative closet point (ICP)-based co-registration approaches for computing anapproximated sourcemodel using single and multiple available brain MRI scans.We also evaluated the two different template MRI selection strategies: one is basedon objective registration error, and another on sourcemodel approximation error.The outcome suggests that averaged approximated solutions using multiple templatebrain MRI scans showed better performance than single-template MRIbasedsolutions. The FID-based approach performed better than the ICP-basedapproach for co-registration of the digitized head surface and brain MRI scan.While selecting template MRIs, the selection approach based on objective registrationerror showed better performance than a sourcemodel approximation errorbasedcriterion. Cross-dataset performance analysis showed a higher modelapproximation error than within-dataset analysis. In conclusion, the FID-basedco-registration approach and objective registration error-based MRI selection criteriaprovide a simple, fast and more accurate solution to compute averagedapproximated models compared with the ICP-based approach. The demographyof brain MRI scans should be similar to that of the query subject whose brainMRI scan was unavailable.