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Updated: Apr 1, 2026
Detecting Pre-Stimulus Source-Level Effects on Object Perception with Magnetoencephalography
Published on: July 26, 2019
A multicenter study of the early detection of synaptic dysfunction in Mild Cognitive Impairment using
Fernando Maestú1, Jose-Maria Peña1, Pilar Garcés1
1Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Complutense University of Madrid and Technical University of Madrid, Madrid, Spain.
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.
Insights
Magnetoencephalography (MEG) identified neuronal hypersynchronization in Mild Cognitive Impairment (MCI) patients. This pattern, involving fronto-parietal and interhemispheric links, may serve as an early biomarker for Alzheimer's-type dementia.
Area of Science:
- Neuroscience
- Biomarkers
- Medical Imaging
Background:
- Synaptic disruption is an early indicator of Alzheimer's-type dementia (DAT).
- Mild Cognitive Impairment (MCI) shows group-level network synchronization changes, but individual-level discrimination using Magnetoencephalography (MEG) is underexplored.
Purpose of the Study:
- To discriminate individuals with MCI from normal aging using MEG and functional connectivity.
- To identify reliable preclinical biomarkers for MCI and DAT.
Main Methods:
- An international multicenter study utilizing MEG data.
- Classification of MCI subjects using features (links) from a trained dataset across five centers.
- Analysis of functional connectivity metrics to detect network synchronization patterns.
Main Results:
- A distinct pattern of neuronal hypersynchronization was identified in MCI patients.
- Fronto-parietal and interhemispheric functional connectivity links were key discriminators.
- The observed hypersynchronization pattern was consistent across multiple independent MEG centers.
Conclusions:
- Neuronal hypersynchronization is a stable, cross-center finding in MCI.
- This pattern represents an early sign of synaptic disruption.
- The identified MEG-based pattern shows potential as a preclinical biomarker for MCI/DAT.
