UNIGE document Scientific Article
previous document  unige:83553  next document
add to browser collection
Title

Classification of Single Normal and Alzheimer's Disease Individuals from Cortical Sources of Resting State EEG Rhythms

Authors
Babiloni, Claudio
Triggiani, Antonio I.
Lizio, Roberta
Cordone, Susanna
Tattoli, Giacomo
Bevilacqua, Vitoantonio
Soricelli, Andrea
Ferri, Raffaele
show hidden authors show all authors [1 - 23]
Published in Frontiers in Neuroscience. 2016, vol. 10
Abstract Previous studies have shown abnormal power and functional connectivity of resting state electroencephalographic (EEG) rhythms in groups of Alzheimer's disease (AD) compared to healthy elderly (Nold) subjects. Here we tested the best classification rate of 120 AD patients and 100 matched Nold subjects using EEG markers based on cortical sources of power and functional connectivity of these rhythms. EEG data were recorded during resting state eyes-closed condition. Exact low-resolution brain electromagnetic tomography (eLORETA) estimated the power and functional connectivity of cortical sources in frontal, central, parietal, occipital, temporal, and limbic regions. Delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-10.5 Hz), alpha 2 (10.5-13 Hz), beta 1 (13-20 Hz), beta 2 (20-30 Hz), and gamma (30-40 Hz) were the frequency bands of interest. The classification rates of interest were those with an area under the receiver operating characteristic curve (AUROC) higher than 0.7 as a threshold for a moderate classification rate (i.e., 70%). Results showed that the following EEG markers overcame this threshold: (i) central, parietal, occipital, temporal, and limbic delta/alpha 1 current density; (ii) central, parietal, occipital temporal, and limbic delta/alpha 2 current density; (iii) frontal theta/alpha 1 current density; (iv) occipital delta/alpha 1 inter-hemispherical connectivity; (v) occipital-temporal theta/alpha 1 right and left intra-hemispherical connectivity; and (vi) parietal-limbic alpha 1 right intra-hemispherical connectivity. Occipital delta/alpha 1 current density showed the best classification rate (sensitivity of 73.3%, specificity of 78%, accuracy of 75.5%, and AUROC of 82%). These results suggest that EEG source markers can classify Nold and AD individuals with a moderate classification rate higher than 80%.
Keywords Alzheimer's disease (AD)Alpha rhythmsArea under the receiver operating characteristic curve (AUROC)Delta rhythmsElectroencephalography (EEG)Exact low-resolution brain electromagnetic tomography (eLORETA)Lagged linear connectivitySpectral coherence
Identifiers
Full text
Structures
Research group Troubles de mémoire et maladie d'Alzeimer (935)
Citation
(ISO format)
BABILONI, Claudio et al. Classification of Single Normal and Alzheimer's Disease Individuals from Cortical Sources of Resting State EEG Rhythms. In: Frontiers in Neuroscience, 2016, vol. 10. https://archive-ouverte.unige.ch/unige:83553

106 hits

1 download

Update

Deposited on : 2016-05-09

Export document
Format :
Citation style :