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A multicenter study of the early detection of synaptic dysfunction in Mild Cognitive Impairment using Magnetoencephalography-derived functional connectivity.
Maestú, Fernando; Peña, Jose-Maria; Garcés, Pilar; González, Santiago; Bajo, Ricardo; Bagic, Anto; Cuesta, Pablo; Funke, Michael; Mäkelä, Jyrki P; Menasalvas, Ernestina; Nakamura, Akinori; Parkkonen, Lauri; López, Maria E; Del Pozo, Francisco; Sudre, Gustavo; Zamrini, Edward; Pekkonen, Eero; Henson, Richard N; Becker, James T.
Afiliação
  • Maestú F; Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Complutense University of Madrid and Technical University of Madrid, Madrid, Spain.
  • Peña JM; Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Complutense University of Madrid and Technical University of Madrid, Madrid, Spain.
  • Garcés P; Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Complutense University of Madrid and Technical University of Madrid, Madrid, Spain.
  • González S; Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Complutense University of Madrid and Technical University of Madrid, Madrid, Spain.
  • Bajo R; Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Complutense University of Madrid and Technical University of Madrid, Madrid, Spain.
  • Bagic A; Department of Neurology, University of Pittsburgh, Pittsburgh, USA.
  • Cuesta P; Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Complutense University of Madrid and Technical University of Madrid, Madrid, Spain.
  • Funke M; Department of Pediatrics, University of Texas Health Science Center, Houston, USA.
  • Mäkelä JP; BioMag Laboratory, HUS Medical Imaging Center, Helsinki University Central Hospital, Hensinki, Finland.
  • Menasalvas E; Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Complutense University of Madrid and Technical University of Madrid, Madrid, Spain.
  • Nakamura A; Department of Clinical and Experimental Neuroimaging, National Center for Geriatrics and Gerontology, Obu, Japan.
  • Parkkonen L; Department of Biomedical Engineering and Computational Science, Aalto University School of Science, Aalto, Espoo, Finland ; Elekta Oy, Helsinki, Finland.
  • López ME; Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Complutense University of Madrid and Technical University of Madrid, Madrid, Spain.
  • Del Pozo F; Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Complutense University of Madrid and Technical University of Madrid, Madrid, Spain.
  • Sudre G; Human Genome Research Institute, National Institutes of Health, Bethesda, USA.
  • Zamrini E; Department of Neurology, University of Utah, Salt Lake City, USA.
  • Pekkonen E; Department of Neurology, University of Helsinki, Finland.
  • Henson RN; Medical Research Council Cognition and Brain Sciences Unit, Cambridge, UK.
  • Becker JT; Department of Neurology, University of Pittsburgh, Pittsburgh, USA ; Department of Psychiatry, University of Pittsburgh, Pittsburgh, USA ; Department of Psychology, University of Pittsburgh, Pittsburgh, USA.
Neuroimage Clin ; 9: 103-9, 2015.
Article em En | MEDLINE | ID: mdl-26448910
Synaptic disruption is an early pathological sign of the neurodegeneration of Dementia of the Alzheimer's type (DAT). The changes in network synchronization are evident in patients with Mild Cognitive Impairment (MCI) at the group level, but there are very few Magnetoencephalography (MEG) studies regarding discrimination at the individual level. In an international multicenter study, we used MEG and functional connectivity metrics to discriminate MCI from normal aging at the individual person level. A labeled sample of features (links) that distinguished MCI patients from controls in a training dataset was used to classify MCI subjects in two testing datasets from four other MEG centers. We identified a pattern of neuronal hypersynchronization in MCI, in which the features that best discriminated MCI were fronto-parietal and interhemispheric links. The hypersynchronization pattern found in the MCI patients was stable across the five different centers, and may be considered an early sign of synaptic disruption and a possible preclinical biomarker for MCI/DAT.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Sinapses / Encéfalo / Disfunção Cognitiva Tipo de estudo: Clinical_trials / Diagnostic_studies / Prognostic_studies / Screening_studies Limite: Aged / Female / Humans / Male Idioma: En Ano de publicação: 2015 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Sinapses / Encéfalo / Disfunção Cognitiva Tipo de estudo: Clinical_trials / Diagnostic_studies / Prognostic_studies / Screening_studies Limite: Aged / Female / Humans / Male Idioma: En Ano de publicação: 2015 Tipo de documento: Article