2026-09-19T20:40:24Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/405282022-01-13T07:54:29Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Emery N. Brown and Matti Hämäläinen.
Molins Jiménez, Antonio
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2008-02-27T22:43:36Z
2008-02-27T22:43:36Z
2007
2007
http://hdl.handle.net/1721.1/40528
191912581
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.
Includes bibliographical references (leaves 69-74).
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.
by Antonio Molins Jiménez.
S.M.
74 leaves
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Multimodal integration of EEG and MEG data using minimum ℓ₂-norm estimates
Multimodal integration of electroencephalography and magnetoencephalography data using minimum ℓ₂-norm estimates
Thesis
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