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Basic Science and Pathogenesis.

Xiaoyan Liang1, Xuewen Xiao1, Cong Zhang1

  • 1Xiangya Hospital, Central South University, Changsha, Hunan, China.

Alzheimer'S & Dementia : the Journal of the Alzheimer'S Association
|December 23, 2025
PubMed
Summary
This summary is machine-generated.

Quantitative differences in resting-state electroencephalography (EEG) distinguish cognitively normal (CN) from cognitively impaired (CI) elderly individuals. These EEG markers are independently associated with cognitive performance, offering potential for early dementia detection.

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Area of Science:

  • Neuroscience
  • Gerontology
  • Biomedical Engineering

Background:

  • Electroencephalography (EEG) is crucial for studying neurological disorders.
  • Quantitative EEG (qEEG) differences between cognitively normal (CN) and cognitively impaired (CI) elderly populations require further investigation.
  • Identifying early EEG changes may elucidate electrophysiological alterations and mechanisms in dementia pathogenesis.

Purpose of the Study:

  • To investigate quantitative differences in resting-state EEG between CN and CI elderly individuals.
  • To determine the association between specific EEG indices and cognitive performance.
  • To explore the potential of EEG as an early biomarker for cognitive decline.

Main Methods:

  • Resting-state EEG data were collected from 685 elderly participants (300 CN, 385 CI) using an NVX19 electroencephalograph.
  • EEG data were analyzed for peak frequency and band power across 19 electrodes using DAFCAR software.
  • Cognitive function was assessed using the Mini-Mental State Examination (MMSE), with adjustments for education level. APOE ε4 genotype was also analyzed.

Main Results:

  • Initially, 21 EEG indices showed significant differences between CN and CI groups (p < 0.05).
  • After adjusting for demographic and genetic factors, 20 EEG indices remained significantly correlated with MMSE scores.
  • Specific findings include negative correlation of fronto-central Alpha with MMSE and positive correlation of temporal Alpha. Beta sub-bands (Beta1, Beta2) exhibited complex regional patterns.

Conclusions:

  • Resting-state EEG features significantly differ between cognitively normal and impaired elderly individuals.
  • These EEG features are independently associated with cognitive performance.
  • qEEG analysis holds promise for identifying early electrophysiological changes related to cognitive impairment and dementia.