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      Searching for Primary Predictors of Conversion from Mild Cognitive Impairment to Alzheimer’s Disease: A Multivariate Follow-Up Study

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          Most cited references44

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          Spatiotemporal signal space separation method for rejecting nearby interference in MEG measurements.

          Limitations of traditional magnetoencephalography (MEG) exclude some important patient groups from MEG examinations, such as epilepsy patients with a vagus nerve stimulator, patients with magnetic particles on the head or having magnetic dental materials that cause severe movement-related artefact signals. Conventional interference rejection methods are not able to remove the artefacts originating this close to the MEG sensor array. For example, the reference array method is unable to suppress interference generated by sources closer to the sensors than the reference array, about 20-40 cm. The spatiotemporal signal space separation method proposed in this paper recognizes and removes both external interference and the artefacts produced by these nearby sources, even on the scalp. First, the basic separation into brain-related and external interference signals is accomplished with signal space separation based on sensor geometry and Maxwell's equations only. After this, the artefacts from nearby sources are extracted by a simple statistical analysis in the time domain, and projected out. Practical examples with artificial current dipoles and interference sources as well as data from real patients demonstrate that the method removes the artefacts without altering the field patterns of the brain signals.
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            VALIDITY OF THE TRAIL MAKING TEST AS AN INDICATOR OF ORGANIC BRAIN DAMAGE

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              The magnetic lead field theorem in the quasi-static approximation and its use for magnetoencephalography forward calculation in realistic volume conductors.

              The equation for the magnetic lead field for a given magnetoencephalography (MEG) channel is well known for arbitrary frequencies omega but is not directly applicable to MEG in the quasi-static approximation. In this paper we derive an equation for omega = 0 starting from the very definition of the lead field instead of using Helmholtz's reciprocity theorems. The results are (a) the transpose of the conductivity times the lead field is divergence-free, and (b) the lead field differs from the one in any other volume conductor by a gradient of a scalar function. Consequently, for a piecewise homogeneous and isotropic volume conductor, the lead field is always tangential at the outermost surface. Based on this theoretical result, we formulated a simple and fast method for the MEG forward calculation for one shell of arbitrary shape: we correct the corresponding lead field for a spherical volume conductor by a superposition of basis functions, gradients of harmonic functions constructed here from spherical harmonics, with coefficients fitted to the boundary conditions. The algorithm was tested for a prolate spheroid of realistic shape for which the analytical solution is known. For high order in the expansion, we found the solutions to be essentially exact and for reasonable accuracies much fewer multiplications are needed than in typical implementations of the boundary element methods. The generalization to more shells is straightforward.

                Author and article information

                Journal
                Journal of Alzheimer's Disease
                JAD
                IOS Press
                13872877
                18758908
                April 26 2016
                April 26 2016
                : 52
                : 1
                : 133-143
                Affiliations
                [1 ]Laboratory of Neuropsychology, Universitat de les Illes Balears, Palma de Mallorca, Spain
                [2 ]Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Complutense University of Madrid and Technical University of Madrid, Spain
                [3 ]Institute of Sanitary Investigation [IdISSC], San Carlos University Hospital, Madrid, Spain
                [4 ]Department of Biostatistics and Operational Investigation, Complutense University of Madrid, Spain
                [5 ]Department of Basic Psychology II, Complutense University of Madrid, Spain
                [6 ]Neurology Department, San Carlos University Hospital, Madrid, Spain
                [7 ]Geriatrics Department, San Carlos University Hospital, Madrid, Spain
                [8 ]Radiology Department, San Carlos University Hospital, Madrid, Spain
                [9 ]Laboratory of Psychoneuroendocrinology and Molecular Genetics, Biomedical Research Foundation, San Carlos University Hospital, Madrid, Spain
                [10 ]Department of Psychiatry, Faculty of Medicine, Complutense University of Madrid, Spain
                Article
                10.3233/JAD-151034
                5fb0ff44-cfe3-4fe6-9e1a-f268f2f46049
                © 2016
                History

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