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%.
Highlights
Subjects’ age, education, individual alpha frequency (IAF), and gender were used as covariates
The results of the first statistical session showed that compared to the normal elderly (Nold) group, the Alzheimer’s disease (AD) group was characterized by higher delta source activity and lower alpha 1 source activity in several cortical regions, as well as higher theta activity in frontal region
The present results suggest that EEG markers of source power and functional connectivity in relaxed wakefulness may enrich the neurophysiological assessment of AD patients with dementia, the best EEG marker for the classification between Nold and AD individuals was the occipital sources of delta/low frequency alpha
Summary
Criteria for clinical diagnosis of AD were proposed in 1984 (McKhann et al, 1984) by the National Institute of Neurological and Communicative Disorders and Stroke (NINCDS) and by the Alzheimer’s Disease and Related Disorders Association (ADRDA). The mentioned PET and MRI methodologies capture several processes of AD, but cannot be always used due to the limited availability of the instrumental resources, costs, invasiveness, or radiation exposure (e.g., PET). These limitations are problematic especially for serial recordings over time. As an important methodological limitation, recorded EEG data require an expert manual verification of the EEG epochs free from artifacts, and commercial pieces of software do not provide immediate statistical indexes of abnormalities of EEG markers with respect to a normative database
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