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

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Maestu , F , Pena , J-M , Garces , P , Gonzalez , S , Bajo , R , Bagic , A , Cuesta , P , Funke , M , Makela , J P , Menasalvas , E , Nakamura , A , Parkkonen , L , Lopez , M E , del Pozo , F , Sudre , G , Zamrini , E , Pekkonen , E , Henson , R N , Becker , J T & Magnetoencephalography Int 2015 , ' A multicenter study of the early detection of synaptic dysfunction in Mild Cognitive Impairment using Magnetoencephalography-derived functional connectivity ' , NeuroImage: Clinical , vol. 9 , pp. 103-109 . https://doi.org/10.1016/j.nicl.2015.07.011

Title: A multicenter study of the early detection of synaptic dysfunction in Mild Cognitive Impairment using Magnetoencephalography-derived functional connectivity
Author: Maestu, Fernando; Pena, Jose-Maria; Garces, Pilar; Gonzalez, Santiago; Bajo, Ricardo; Bagic, Anto; Cuesta, Pablo; Funke, Michael; Makela, Jyrki P.; Menasalvas, Ernestina; Nakamura, Akinori; Parkkonen, Lauri; Lopez, Maria E.; del Pozo, Francisco; Sudre, Gustavo; Zamrini, Edward; Pekkonen, Eero; Henson, Richard N.; Becker, James T.; Magnetoencephalography Int
Contributor: University of Helsinki, BioMag Laboratory
University of Helsinki, Neurologian yksikkö
Date: 2015
Language: eng
Number of pages: 7
Belongs to series: NeuroImage: Clinical
ISSN: 2213-1582
URI: http://hdl.handle.net/10138/223945
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. (C) 2015 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons. org/licenses/by-nc-nd/4.0/).
Subject: Magnetoencephalography
Mild Cognitive Impairment
Functional connectivity
Data mining
Machine learning
Synaptic dysfunction
Multicenter study
SIGNAL SPACE SEPARATION
RESTING-STATE FMRI
ALZHEIMERS-DISEASE
NEURODEGENERATION
CLASSIFICATION
VALIDATION
NETWORK
3112 Neurosciences
3124 Neurology and psychiatry
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