Affiliations: [a] Department of Neurology, Prof. Kornel Gibiński University Clinical Center, Medical University of Silesia, Katowice, Poland
| [b] Faculty of Biomedical Engineering, Silesian University of Technology, Zabrze, Poland
| [c] Department of Imaging Diagnostics and Interventional Radiology, Prof. Kornel Gibiński University Clinical Center, Medical University of Silesia, Katowice, Poland
| [d] Department of Solid State Physics, Faculty of Physics and Applied Computer Science, University of Łódź, Łódź, Poland
| [e] Department of Neurology, Faculty of Medical Sciences in Katowice, Medical University of Silesia, Katowice, Poland
Correspondence:
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Correspondence to: Daniel Ledwoń, Faculty of Biomedical Engineering, Silesian University of Technology, Zabrze, Poland. Tel.: +48 32 277 74 72; E-mail: daniel.ledwon@polsl.pl.
Abstract: 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.
