Multimodal integration of EEG and MEG data using minimum ℓ₂-norm estimates
Author(s)
Molins Jiménez, Antonio
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Alternative title
Multimodal integration of electroencephalography and magnetoencephalography data using minimum ℓ₂-norm estimates
Other Contributors
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Advisor
Emery N. Brown and Matti Hämäläinen.
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The aim of this thesis was to study the effects of multimodal integration of electroencephalography (EEG) and magnetoencephalography (MEG) data on the minimum ℓ₂-norm estimates of cortical current densities. We investigated analytically the effect of including EEG recordings in MEG studies versus the addition of new MEG channels. To further confirm these results, clinical datasets comprising concurrent MEG/EEG acquisitions were analyzed. Minimum ℓ₂-norm estimates were computed using MEG alone, EEG alone, and the combination of the two modalities. Localization accuracy of responses to median-nerve stimulation was evaluated to study the utility of combining MEG and EEG.
Description
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007. Includes bibliographical references (leaves 69-74).
Date issued
2007Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer SciencePublisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.