Resting state EEG biomarkers of cognitive decline associated with Alzheimer’s disease and mild cognitive impairment

Abstract

In this paper, we explore the utility of resting-state EEG measures as potential biomarkers for the detection and assessment of cognitive decline in mild cognitive impairment (MCI) and Alzheimer’s disease (AD). Neurophysiological biomarkers of AD derived from EEG and FDG-PET, once characterized and validated, would expand the set of existing diagnostic molecular biomarkers of AD pathology with associated biomarkers of disease progression and neural dysfunction. Since symptoms of AD often begin to appear later in life, successful identification of EEG-based biomarkers must account for age-related neurophysiological changes that occur even in healthy individuals. To this end, we collected EEG data from individuals with AD (n = 26), MCI (n = 53), and cognitively normal healthy controls stratified by age into three groups: 18–40 (n = 129), 40–60 (n = 62) and 60–90 (= 55) years old. For each participant, we computed power spectral density at each channel and spectral coherence between pairs of channels. Compared to age matched controls, in the AD group, we found increases in both spectral power and coherence at the slower frequencies (Delta, Theta). A smaller but significant increase in power of slow frequencies was observed for the MCI group, localized to temporal areas. These effects on slow frequency spectral power opposed that of normal aging observed by a decrease in the power of slow frequencies in our control groups. The AD group showed a significant decrease in the spectral power and coherence in the Alpha band consistent with the same effect in normal aging. However, the MCI group did not show any significant change in the Alpha band. Overall, Theta to Alpha ratio (TAR) provided the largest and most significant differences between the AD group and controls. However, differences in the MCI group remained small and localized. We proposed a novel method to quantify these small differences between Theta and Alpha bands’ power using empirically derived distributions of spectral power across the time domain as opposed to averaging power across time. We defined Power Distribution Distance Measure (PDDM) as a distance measure between probability distribution functions (pdf) of Theta and Alpha power. Compared to average TAR, using PDDF enhanced the statistical significance, the effect size, and the spatial distribution of significant effects in the MCI group. We designed classifiers for differentiating individual MCI and AD participants from age-matched controls. The classification performance measured by the area under ROC curve after cross-validation were AUC = 0.85 and AUC = 0.6, for AD and MCI classifiers, respectively. Posterior probability of AD, TAR, and the proposed PDDM measure were all significantly correlated with MMSE score and neuropsychological tests in the AD group.

The effect of a psychomotor intervention on electroencephalography and neuropsychological performances in older adults with and without mild cognitive impairment

“…However, no persistent and meaningful correlation between RAVLT and EEG variables was determined. Previous studies shown correlations between resting‐state EEG power and cognitive functions in individuals with AD, but not in individuals with MCI 17,45 . Therefore, cognitive deficits present in individuals with MCI may not be severe enough to be detected by resting‐state EEG recordings.…”

Simultaneous pathway engagement of translation in astrocytes, circadian rhythm in GABAergic neurons and cytoskeleton in glutamatergic neurons precede electroencephalographic changes in neurodegenerative prion disease

“…EEG measures the summarized electrical activity of cortical and subcortical neurons, providing a very sensitive tool to detect brain dysfunction (Leuchter et al, 2017; Meghdadi et al, 2021), including theta power increases in several human PrDs (Franko et al, 2016). Analyses of EEG spectral frequency distributions revealed a pronounced and progressive increase in the theta band (5-10 Hz) relative to other frequencies (0-50 Hz) that reached statistical significance at 18 weeks post-injection (WPI) (Fig 1C).…”

Predicting Dementia With Prefrontal Electroencephalography and Event-Related Potential

“…For instance, the study of Garn et al (2014) explained 36%-51% of the variances associated with quantitative EEG markers by using MMSE scores and exhibited a strong correlation between MMSE scores and event-related potential (ERP) face-name encoding task. There was a significant negative correlation between MMSE scores with the temporal theta to alpha ratio, with r = −0.69 in AD group (Meghdadi et al, 2021). Significant correlations of MMSE with EEG beta activity were also observed (Lees et al, 2016) along with P300 latency (Tanaka et al, 1998;Lee et al, 2013).…”