ArticleAlzheimer's research & therapy2023
Neurophysiological markers in community-dwelling older adults with mild cognitive impairment: an EEG study.
Article in Alzheimer's research & therapy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.
- Electroencephalography in Subjective Cognitive Decline and Mild Cognitive Impairment: Systematic Review of Biomarkers, Classification, and Prognostic Evidence.Journal of medical Internet research · 2026Pooled it
- Wearable-Compatible Detection of Mild Cognitive Impairment Using Novel Features Based on Sleep Stage Dynamics.Brain sciences · 2026Article
- Fusion of Multi-Paradigm EEG Microstate Features to Enhance the Recognition of Mild Cognitive Impairment.Brain and behavior · 2026Article
- Detection of neurophysiological markers of cognitive reserve: an EEG study.Frontiers in aging neuroscience · 2024Article
Corrections and comments
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Authors and funding
14 authors at 4 institutions in 2 countries.
Funding
Abstract
backgroundNeurodegeneration and structural changes in the brain due to amyloid deposition have been observed even in individuals with mild cognitive impairment (MCI). EEG measurement is considered an effective tool because it is noninvasive, has few restrictions on the measurement environment, and is simple and easy to use. In this study, we investigated the neurophysiological characteristics of community-dwelling older adults with MCI using EEG.
methodsDemographic characteristics, cognitive function, physical function, resting-state MRI and electroencephalogram (rs-EEG), event-related potentials (ERPs) during Simon tasks, and task proportion of correct responses and reaction times (RTs) were obtained from 402 healthy controls (HC) and 47 MCI participants. We introduced exact low-resolution brain electromagnetic tomography-independent component analysis (eLORETA-ICA) to assess the rs-EEG network in community-dwelling older adults with MCI.
resultsA lower proportion of correct responses to the Simon task and slower RTs were observed in the MCI group (p < 0.01). Despite no difference in brain volume between the HC and MCI groups, significant decreases in dorsal attention network (DAN) activity (p < 0.05) and N2 amplitude of ERP (p < 0.001) were observed in the MCI group. Moreover, DAN activity demonstrated a correlation with education (Rs = 0.32, p = 0.027), global cognitive function (Rs = 0.32, p = 0.030), and processing speed (Rs = 0.37, p = 0.010) in the MCI group. The discrimination accuracy for MCI with the addition of the eLORETA-ICA network ranged from 0.7817 to 0.7929, and the area under the curve ranged from 0.8492 to 0.8495.
conclusionsThe eLORETA-ICA approach of rs-EEG using noninvasive and relatively inexpensive EEG demonstrates specific changes in elders with MCI. It may provide a simple and valid assessment method with few restrictions on the measurement environment and may be useful for early detection of MCI in community-dwelling older adults.
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