Abstract
Electroencephalography (EEG) has shown potential for identifying early-stage biomarkers of neurocognitive dysfunction associated with dementia due to Alzheimer's disease (AD). A large body of evidence shows that, compared to healthy controls (HC), AD is associated with power increases in lower EEG frequencies (delta and theta) and decreases in higher frequencies (alpha and beta), together with slowing of the peak alpha frequency. However, the pathophysiological processes underlying these changes remain unclear. For instance, recent studies have shown that apparent shifts in EEG power from high to low frequencies can be driven either by frequency specific periodic power changes or rather by non-oscillatory (aperiodic) changes in the underlying 1/f slope of the power spectrum. Hence, to clarify the mechanism(s) underlying the EEG alterations associated with AD, it is necessary to account for both periodic and aperiodic characteristics of the EEG signal. Across two independent datasets, we examined whether resting-state EEG changes linked to AD reflect true oscillatory (periodic) changes, changes in the aperiodic (non-oscillatory) signal, or a combination of both. We found strong evidence that the alterations are purely periodic in nature, with decreases in oscillatory power at alpha and beta frequencies (AD < HC) leading to lower (alpha + beta) / (delta + theta) power ratios in AD. Aperiodic EEG features did not differ between AD and HC. By replicating the findings in two cohorts, we provide robust evidence for purely oscillatory pathophysiology in AD and against aperiodic EEG changes. We therefore clarify the alterations underlying the neural dynamics in AD and emphasize the robustness of oscillatory AD signatures, which may further be used as potential prognostic or interventional targets in future clinical investigations.
Original language | English |
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Article number | 106380 |
Journal | Neurobiology of Disease |
Volume | 190 |
Early online date | 17 Dec 2023 |
DOIs | |
Publication status | Published - 31 Jan 2024 |
Funding
M.K. was supported by a Vacation Scholarship from The Carnegie Trust for The Universities of Scotland ( VAC010474 ). C.S.Y·B was supported by the British Academy/Leverhulme Trust and the United Kingdom Department for Business, Energy, and Industrial Strategy ( SRG19/191169 ). S.S.B. was supported by the NIH ( 1K23AG068384-01A1 ) and the Alzheimer's Association ( 2019-AACSF-643094 ). M.M.S. was supported by the NIH ( NIA P01AG031720-8405 ). A.P.L. is partly supported by grants from the NIH ( R01AG076708 , R03AG072233 ) and BrightFocus Foundation . The data was collected with support from the following grants: NIH-NINDS R21NS082870 , NIH-NIMH R01MH115949-S1 , NIH-NIA R21AG051846 , and NIA R01AG060987 .
Funders | Funder number |
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NIH-NIA | R21AG051846, R01AG060987 |
NIH-NIMH | R01MH115949-S1 |
National Institutes of Health | 1K23AG068384-01A1 |
National Institute of Neurological Disorders and Stroke | R21NS082870 |
Alzheimer's Association | 2019-AACSF-643094 |
BrightFocus Foundation | |
Department for Business, Energy & Industrial Strategy | SRG19/191169 |
Leverhulme Trust | |
Carnegie Trust for the Universities of Scotland | VAC010474 |
NHS Innovation Accelerator | R03AG072233, R01AG076708, P01AG031720-8405 |
Keywords
- Alzheimer's
- Dementia
- EEG
- Oscillations
ASJC Scopus subject areas
- Neurology