Journal of Alzheimer's disease : JAD · 2024
Quantitative EEG Spectral and Connectivity Analysis for Cognitive Decline in Amnestic Mild Cognitive Impairment.
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Zawiślak-Fornagiel Katarzyna, Ledwoń Daniel, Bugdol Monika, Grażyńska Anna, Ślot Maciej, Tabaka-Pradela Justyna, Bieniek Izabela, Siuda Joanna
Аннотация
BACKGROUND: Mild cognitive impairment (MCI) is considered to be the borderline of cognitive changes associated with aging and very early dementia. Cognitive functions in MCI can improve, remain stable or progress to clinically probable AD. Quantitative electroencephalography (qEEG) can become a useful tool for using the analytical techniques to quantify EEG patterns indicating cognitive impairment.
OBJECTIVE: The aim of our study was to assess spectral and connectivity analysis of the EEG resting state activity in amnestic MCI (aMCI) patients in comparison with healthy control group (CogN).
METHODS: 30 aMCI patients and 23 CogN group, matched by age and education, underwent equal neuropsychological assessment and EEG recording, according to the same protocol.
RESULTS: qEEG spectral analysis revealed decrease of global relative beta band power and increase of global relative theta and delta power in aMCI patients. Whereas, decreased coherence in centroparietal right area considered to be an early qEEG biomarker of functional disconnection of the brain network in aMCI patients. In conclusion, the demonstrated changes in qEEG, especially, the coherence patterns are specific biomarkers of cognitive impairment in aMCI.
CONCLUSIONS: Therefore, qEEG measurements appears to be a useful tool that complements neuropsychological diagnostics, assessing the risk of progression and provides a basis for possible interventions designed to improve cognitive functions or even inhibit the progression of the disease.
OBJECTIVE: The aim of our study was to assess spectral and connectivity analysis of the EEG resting state activity in amnestic MCI (aMCI) patients in comparison with healthy control group (CogN).
METHODS: 30 aMCI patients and 23 CogN group, matched by age and education, underwent equal neuropsychological assessment and EEG recording, according to the same protocol.
RESULTS: qEEG spectral analysis revealed decrease of global relative beta band power and increase of global relative theta and delta power in aMCI patients. Whereas, decreased coherence in centroparietal right area considered to be an early qEEG biomarker of functional disconnection of the brain network in aMCI patients. In conclusion, the demonstrated changes in qEEG, especially, the coherence patterns are specific biomarkers of cognitive impairment in aMCI.
CONCLUSIONS: Therefore, qEEG measurements appears to be a useful tool that complements neuropsychological diagnostics, assessing the risk of progression and provides a basis for possible interventions designed to improve cognitive functions or even inhibit the progression of the disease.