EEG spectral power abnormalities and their relationship with cognitive dysfunction in patients with Alzheimer’s disease and type 2 diabetes

Christopher S. Y. Benwell (Lead / Corresponding author), Paula Davila-Perez, Peter J. Fried, Richard N. Jones, Thomas G. Travison, Emiliano Santarnecchi, Alvaro Pascual-Leone, Mouhsin M. Shafi

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Abstract

Rhythmic neural activity has been proposed to play a fundamental role in cognition. Both healthy and pathological aging are characterized by frequency-specific changes in oscillatory activity. However, the cognitive relevance of these changes across the spectrum from normal to pathological aging remains unknown. We examined electroencephalography (EEG) correlates of cognitive function in healthy aging and 2 of the most prominent and debilitating age-related disorders: type 2 diabetes mellitus (T2DM) and Alzheimer's disease (AD). Relative to healthy controls (HC), patients with AD were impaired on nearly every cognitive measure, whereas patients with T2DM performed worse mainly on learning and memory tests. A continuum of alterations in resting-state EEG was associated with pathological aging, generally characterized by reduced alpha (α) and beta (β) power (AD < T2DM < HC) and increased delta (δ) and theta (θ) power (AD > T2DM > HC), with some variations across different brain regions. There were also reductions in the frequency and power density of the posterior dominant rhythm in AD. The ratio of (α + β)/(δ + θ) was specifically associated with cognitive function in a domain- and diagnosis-specific manner. The results thus captured both similarities and differences in the pathophysiology of cerebral oscillations in T2DM and AD. Overall, pathological brain aging is marked by a shift in oscillatory power from higher to lower frequencies, which can be captured by a single cognitively relevant measure of the ratio of (α + β) over (δ + θ) power.

Original languageEnglish
Pages (from-to)83-95
Number of pages13
JournalNeurobiology of Aging
Volume85
Early online date14 Oct 2019
DOIs
Publication statusPublished - Jan 2020

Keywords

  • Alzheimer's disease
  • Cognitive aging
  • EEG
  • Neuropsychology
  • Oscillations
  • Type-2 diabetes mellitus

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