Medizinische Universität Graz Austria/Österreich - Forschungsportal - Medical University of Graz
Gewählte Publikation:
SHR Neuro Krebs Kardio Lipid Stoffw Microb
Waser, M; Garn, H; Deistler, M; Benke, T; Dal-Bianco, P; Ransmayr, G; Schmidt, H; Sanin, G; Santer, P; Caravias, G; Seiler, S; Grossegger, D; Fruehwirt, W; Schmidt, R.
Using static and dynamic canonical correlation coefficients as quantitative EEG markers for Alzheimer's disease severity.
Conf Proc IEEE Eng Med Biol Soc. 2014; 2014(12):2801-2804
Doi: 10.1109/EMBC.2014.6944205
PubMed
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- Co-Autor*innen der Med Uni Graz
- Schmidt Helena
- Schmidt Reinhold
- Seiler Stephan
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- Abstract:
- We analyzed the relation between Alzheimer's disease (AD) severity as measured by Mini-Mental State Examination (MMSE) scores and quantitative electroencephalographic (qEEG) markers that were derived from canonical correlation analysis. This allowed an investigation of EEG synchrony between groups of EEG channels. In this study, we applied the data from 79 participants in the multi-centric cohort study PRODEM-Austria with probable AD. Following a homogeneous protocol, the EEG was recorded both in resting state and during a cognitive task. A quadratic regression model was used to describe the relation between MMSE and the qEEG synchrony markers. This relation was most significant in the δ and θ frequency bands in resting state, and between left-hemispheric central, temporal and parietal channel groups during the cognitive task. Here, the MMSE explained up to 40% of the qEEG marker's variation. QEEG markers showed an ambiguous trend, i.e. an increase of EEG synchrony in the initial stage of AD (MMSE>20) and a decrease in later stages. This effect could be caused by compensatory brain mechanisms. We conclude that the proposed qEEG markers are closely related to AD severity. Despite the ambiguous trend and the resulting diagnostic ambiguity, the qEEG markers could provide aid in the diagnostics of early-stage AD.
- Find related publications in this database (using NLM MeSH Indexing)
- Aged -
- Aged, 80 and over -
- Alzheimer Disease - diagnosis
- Biomarkers - analysis
- Brain - pathology
- Electrodes -
- Electroencephalography - methods
- Female -
- Humans -
- Male -
- Middle Aged -
- Regression Analysis -