A multicenter study of the early detection of synaptic dysfunction in Mild Cognitive Impairment using magnetoencephalography-derived functional connectivity

Fernando Maestú, Jose-Maria Peña, Pilar Garcés, Santiago González, Ricardo Bajo, Anto Bagic, Pablo Cuesta, Michael Funke, Jyrki P. Mäkelä, Ernestina Menasalvas, Akinori Nakamura, Lauri Parkkonen, Maria E. López, Francisco del Pozo, Gustavo Sudre, Edward Zamrini, Eero Pekkonen, Richard N. Henson, James T. Becker

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Abstract

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.
Original languageEnglish
Pages (from-to)103-109
JournalNEUROIMAGE. CLINICAL
Volume9
DOIs
Publication statusPublished - 2015
MoE publication typeA1 Journal article-refereed

Keywords

  • Magnetoencephalography
  • Mild Cognitive Impairment
  • Functional connectivity
  • Data mining
  • Machine learning
  • Synaptic dysfunction
  • Multicenter study

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