Fronto-parietal coupling of brain rhythms in mild cognitive impairment: A multicentric EEG study

Abstract

Electroencephalographic (EEG) data were recorded in 69 normal elderly (Nold), 88 mild cognitive impairment (MCI), and 109 mild Alzheimer's disease (AD) subjects at rest condition, to test whether the fronto-parietal coupling of EEG rhythms is in line with the hypothesis that MCI can be considered as a pre-clinical stage of the disease at group level. Functional coupling was estimated by synchronization likelihood of Laplacian-transformed EEG data at electrode pairs, which accounts for linear and non-linear components of that coupling. Cortical rhythms of interest were delta (2-4Hz), theta (4-8Hz), alpha 1 (8-10.5Hz), alpha 2 (10.5-13Hz), beta 1 (13-20Hz), beta 2 (20-30Hz), and gamma (30-40Hz). Compared to the Nold subjects, the AD patients presented a marked reduction of the synchronization likelihood (delta to gamma) at both fronto-parietal and inter-hemispherical (delta to beta 2) electrodes. As a main result, alpha 1 synchronization likelihood progressively decreased across Nold, MCI, and mild AD subjects at midline (Fz-Pz) and right (F4-P4) fronto-parietal electrodes. The same was true for the delta synchronization likelihood at right fronto-parietal electrodes (F4-P4). For these EEG bands, the synchronization likelihood correlated with global cognitive status as measured by the Mini Mental State Evaluation. The present results suggest that at group level, fronto-parietal coupling of the delta and alpha rhythms progressively becomes abnormal though MCI and mild AD. Future longitudinal research should evaluate whether the present EEG approach is able to predict the cognitive decline in individual MCI subjects.

A comparative study of synchrony measures for the early diagnosis of Alzheimer's disease based on EEG

“…Section 2.8), is believed to be more sensitive than coherence to detect changes in AD patients (Stam et al, 2003). Using state space based synchrony methods, significant loss of EEG synchrony was found in MCI (Stam et al, 2003) and AD patients (Jeong, 2004;Stam et al, 2003Stam et al, , 2005Babiloni et al, 2006;Pijnenburg et al, 2004;Yagyu et al, 1997;Wan et al, 2008), which evolved consistently from MCI to AD stage (Stam et al, 2003). We report here a low (uncorrected) p-value for the indices N k (p = 0.029; uncorrected) and S k (p = 0.019; uncorrected), and the S-estimator (p = 0.042; uncorrected); however, after post-correction, those effects are not statistically significant.…”

Perspective on future role of biological markers in clinical therapy trials of Alzheimer's disease: A long-range point of view beyond 2020

“…Subtle but consistent deviations in the electromagnetic neuronal dynamics have been shown to precede explicit cognitive manifestations in AD [291] which could enable a future role of EEG/MEG biomarkers not only as a clinical diagnosis and treatment option, but also as a new mode for AD stage discovery. Dramatic progresses in dense-array active-EEG and MEG sensor technology, as well as in advanced signal processing techniques [292] have generated a recent surge of interest to use these promising capabilities in the context of improved clinical AD diagnosis.…”

“…Promising methods involve brain connectivity [296], global synchronization, synchronization likelihood [291], detrended fluctuation analysis, approximate entropy, mutual information, source localization, and a host of further non-linear signal features. This will open new possibilities and raise new questions such as a recent study showing in AD not only that an EEG synchronization marker was suppressed in the 10-30 Hz range (upper-alpha and beta bands) but also that the temporal fluctuations of this synchronization measure carry additional diagnostic value in the lower alpha and beta bands [297].…”

MEG resting state functional connectivity in Parkinson’s disease related dementia

“…Changes in resting state functional connectivity have been demonstrated using EEG and MEG in several brain disorders, including multiple sclerosis ), brain duct tumors (Bartolomei et al 2006), Mild Cognitive Impairment (MCI) (Babiloni et al 2006;Pijnenburg et al 2004;Stam et al 2003) and Alzheimer's disease (AD) Koenig et al 2005;Pijnenburg et al 2004;Babiloni et al 2004;Berendse et al 2000;Locatelli et al 1998;Besthorn et al 1994;Leuchter et al 1992).…”