title: A technique to consider mismatches between fMRI and EEG/MEG sources for fMRI-constrained EEG/MEG source imaging: a preliminary simulation study.
abstract: fMRI-constrained EEG/MEG source imaging can be a powerful tool in studying human brain functions with enhanced spatial and temporal resolutions. Recent studies on the combination of fMRI and EEG/MEG have suggested that fMRI prior information could be readily implemented by simply imposing different weighting factors to cortical sources overlapping with the fMRI activations. It has been also reported, however, that such a hard constraint may cause severe distortions or elimination of meaningful EEG/MEG sources when there are distinct mismatches between the fMRI activations and the EEG/MEG sources. If one wants to obtain the actual EEG/MEG source locations and uses the fMRI prior information as just an auxiliary tool to enhance focality of the distributed EEG/MEG sources, it is reasonable to weaken the strength of fMRI constraint when severe mismatches between fMRI and EEG/MEG sources are observed. The present study suggests an efficient technique to automatically adjust the strength of fMRI constraint according to the mismatch level. The use of the proposed technique rarely affects the results of conventional fMRI-constrained EEG/MEG source imaging if no major mismatch between the two modalities is detected; while the new results become similar to those of typical EEG/MEG source imaging without fMRI constraint if the mismatch level is significant. A preliminary simulation study using realistic EEG signals demonstrated that the proposed technique can be a promising tool to selectively apply fMRI prior information to EEG/MEG source imaging.
authors.affiliation: Department of Biomedical Engineering, Yonsei University, 234 Maejiri, Heungeop-myun, Wonju-si, Kangwon-do, 220-710, Korea. ich@yonsei.ac.kr
authors.forename: Chang-Hwan
authors.initials: CH
authors.lastname: Im
authors.forename: Soo Yeol
authors.initials: SY
authors.lastname: Lee
mesh_terms: D055592:Biophysical Phenomena; D001703:Biophysics; D001921:Brain / Q000033:anatomy & histology / Q000502:physiology; D004569:Electroencephalography / Q000379:methods* / Q000706:statistics & numerical data; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods / Q000706:statistics & numerical data; D008279:Magnetic Resonance Imaging / Q000379:methods* / Q000706:statistics & numerical data; D015225:Magnetoencephalography / Q000379:methods* / Q000706:statistics & numerical data; D008953:Models, Anatomic; D008959:Models, Neurological; D019047:Phantoms, Imaging / Q000706:statistics & numerical data