EEG spectral analysis as a putative early prognostic biomarker in nondemented, amyloid positive subjects

Neurobiol Aging. 2017 Sep;57:133-142. doi: 10.1016/j.neurobiolaging.2017.05.017. Epub 2017 Jun 1.


We studied whether electroencephalography (EEG)-derived measures of brain oscillatory activity are related to clinical progression in nondemented, amyloid positive subjects. We included 205 nondemented amyloid positive subjects (63 subjective cognitive decline [SCD]; 142 mild cognitive impairment [MCI]) with a baseline resting-state EEG data and ≥1-year follow-up. Peak frequency and relative power of 4 frequency bands were calculated. Relationships between normalized EEG measures and time to clinical progression (conversion from SCD to MCI/dementia or from MCI to dementia) were analyzed using Cox proportional hazard models. One hundred eight (53%) subjects clinically progressed after 2.1 (IQR 1.3-3.0) years. In the total sample, none of the EEG spectral measures were significant predictors. Stratified for baseline diagnosis, we found that in SCD patients higher delta and theta power (HR [95% CI] = 1.7 [1.0-2.7] resp. 2.3 [1.2-4.4]), and lower alpha power and peak frequency (HR [95% CI] = 0.5 [0.3-1.0] resp. 0.6 [0.4-1.0]) were associated with clinical progression over time. In amyloid positive subjects with normal cognition, slowing of oscillatory brain activity is related to clinical progression.

Keywords: Alzheimer's disease; Amyloid beta; Clinical progression; Electroencephalography; Prognostic biomarker.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Alzheimer Disease / diagnosis*
  • Alzheimer Disease / metabolism
  • Amyloid beta-Peptides / metabolism*
  • Biomarkers
  • Cognitive Dysfunction / diagnosis
  • Cognitive Dysfunction / metabolism
  • Disease Progression
  • Early Diagnosis
  • Electroencephalography*
  • Female
  • Humans
  • Male
  • Middle Aged
  • Prognosis
  • Proportional Hazards Models


  • Amyloid beta-Peptides
  • Biomarkers