Abstract

BackgroundAlthough numerous electroencephalogram (EEG) studies have described differences in functional connectivity in Alzheimer’s disease (AD) compared to healthy subjects, there is no general consensus on the methodology of estimating functional connectivity in AD. Inconsistent results are reported due to multiple methodological factors such as diagnostic criteria, small sample sizes and the use of functional connectivity measures sensitive to volume conduction. We aimed to investigate the reproducibility of the disease-associated effects described by commonly used functional connectivity measures with respect to the amyloid, tau and neurodegeneration (A/T/N) criteria.MethodsEyes-closed task-free 21-channel EEG was used from patients with probable AD and subjective cognitive decline (SCD), to form two cohorts. Artefact-free epochs were visually selected and several functional connectivity measures (AEC(-c), coherence, imaginary coherence, PLV, PLI, wPLI) were estimated in five frequency bands. Functional connectivity was compared between diagnoses using AN(C)OVA models correcting for sex, age and, additionally, relative power of the frequency band. Another model predicted the Mini-Mental State Exam (MMSE) score of AD patients by functional connectivity estimates. The analysis was repeated in a subpopulation fulfilling the A/T/N criteria, after correction for influencing factors. The analyses were repeated in the second cohort.ResultsTwo large cohorts were formed (SCD/AD; n = 197/214 and n = 202/196). Reproducible effects were found for the AEC-c in the alpha and beta frequency bands (p = 6.20 × 10−7, Cohen’s d = − 0.53; p = 5.78 × 10−4, d = − 0.37) and PLI and wPLI in the theta band (p = 3.81 × 10−8, d = 0.59; p = 1.62 × 10−8, d = 0.60, respectively). Only effects of the AEC-c remained significant after statistical correction for the relative power of the selected bandwidth. In addition, alpha band AEC-c correlated with disease severity represented by MMSE score.ConclusionThe choice of functional connectivity measure and frequency band can have a large impact on the outcome of EEG studies in AD. Our results indicate that in the alpha and beta frequency bands, the effects measured by the AEC-c are reproducible and the most valid in terms of influencing factors, correlation with disease severity and preferable properties such as correction for volume conduction. Phase-based measures with correction for volume conduction, such as the PLI, showed reproducible effects in the theta frequency band.

Highlights

  • Alzheimer’s disease (AD) is the most common cause of dementia, and it is expected that 131.5 million people will be living with dementia in 2050 [1]

  • It is important to evaluate the observed effects of AD on functional connectivity in light of the latest research framework, previously found discrepancies between test results and test-retest reliability issues of some functional connectivity measures. This problem leads to the following question and aim of this study: which functional connectivity measures observe reproducible and valid EEG changes in AD and in which frequency bands do these changes occur? We aimed to answer these questions by designing a study in which we compared commonly used functional connectivity measures with respect to reproducibility, undesirable influence of covariates and correlation with disease severity

  • EEGs were made as part of this process next to clinical assessment, neuropsychological test batteries, magnetic resonance imaging (MRI) or computed tomography scan (CT scan) and, when possible, assessment of amyloid burden by cerebrospinal fluid (CSF) or positron emission tomography (PET)

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Summary

Introduction

Alzheimer’s disease (AD) is the most common cause of dementia, and it is expected that 131.5 million people will be living with dementia in 2050 [1]. Quantitative resting-state EEG data analyses can roughly be divided into three modalities: spectral decomposition, functional connectivity and network-based analyses. Each of these modalities has shown profound changes in AD compared to healthy subjects [2, 5, 6]. There is a broad consensus concerning the typical spectral changes in AD. A broad and general consensus about changes in functional connectivity or brain networks is more complicated. Numerous electroencephalogram (EEG) studies have described differences in functional connectivity in Alzheimer’s disease (AD) compared to healthy subjects, there is no general consensus on the methodology of estimating functional connectivity in AD. We aimed to investigate the reproducibility of the disease-associated effects described by commonly used functional connectivity measures with respect to the amyloid, tau and neurodegeneration (A/T/N) criteria

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