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dc.contributor.advisorEmery N. Brown and Matti Hämäläinen.en_US
dc.contributor.authorMolins Jiménez, Antonioen_US
dc.contributor.otherMassachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2008-02-27T22:43:36Z
dc.date.available2008-02-27T22:43:36Z
dc.date.copyright2007en_US
dc.date.issued2007en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/40528
dc.descriptionThesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.en_US
dc.descriptionIncludes bibliographical references (leaves 69-74).en_US
dc.description.abstractThe 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.en_US
dc.description.statementofresponsibilityby Antonio Molins Jiménez.en_US
dc.format.extent74 leavesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.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.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582
dc.subjectElectrical Engineering and Computer Science.en_US
dc.titleMultimodal integration of EEG and MEG data using minimum ℓ₂-norm estimatesen_US
dc.title.alternativeMultimodal integration of electroencephalography and magnetoencephalography data using minimum ℓ₂-norm estimatesen_US
dc.typeThesisen_US
dc.description.degreeS.M.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.identifier.oclc191912581en_US


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