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Tracking electrophysiological signatures of Alzheimer's disease : a systematic review of multimodal studies

  • Abbas Sohrabpour*
  • , Darko Sarovic
  • , Henrik Zetterberg
  • , Matti S. Hämäläinen
  • , Sylvain Baillet*
  • , Sheraz Khan*
  • *Corresponding author for this work
  • Massachusetts General Hospital
  • University of Gothenburg
  • University College London
  • University of Wisconsin-Madison
  • Hong Kong Center for Neurodegenerative Diseases
  • McGill University
  • Université de Montréal
  • University of Montreal

Research output: Contribution to journalReview Articlepeer-review

2 Citations (Scopus)
2 Downloads (Pure)

Abstract

We conducted a review of the electrophysiological manifestations of Alzheimer's disease (AD) as captured by electroencephalography (EEG) and magnetoencephalography (MEG), with a focus on tracking their evolution through disease progression. To link electrophysiological features to the underlying neurobiology of AD, we prioritized studies that integrated EEG/MEG with other data modalities, such as positron emission tomography (PET) imaging and/or fluid biomarkers (cerebrospinal fluid [CSF] or blood/plasma) of amyloid beta (Aβ) and tau. Our analysis contextualizes these findings within current mechanistic hypotheses of AD pathophysiology. A key highlight of the present review is that electrophysiological changes along the AD disease progression may follow a non-monotonic trajectory, underscoring a need for caution when developing biomarkers for early detection or staging the disease with non-invasive electrophysiology. We also discuss outstanding challenges in the interplay between AD pathology and electrophysiological dynamics. This review highlights the potential of multimodal approaches to refining our understanding of AD and improving its early diagnosis. Highlights: A systematic review of electrophysiological signatures of AD in multimodal studies. Existing findings are contextualized with AD pathophysiology and neurobiology. Electrophysiological signatures of AD evolve in a dynamic, non-linear fashion. (Formula presented.) oscillations show a non-monotonous behavior in different stages of AD progression. EEG/MEG biomarkers hold significant promise for the early detection/monitoring of AD.

Original languageEnglish
Article numbere70835
Pages (from-to)1-23
Number of pages23
JournalAlzheimer's and Dementia
Volume21
Issue number11
DOIs
Publication statusPublished - Nov 2025
MoE publication typeA2 Review article, Literature review, Systematic review

Keywords

  • Alzheimer's disease
  • amyloid beta
  • cross-modal measurements
  • electroencephalogram
  • electrophysiology
  • magnetoencephalogram
  • neuropsychological assessment
  • resting state
  • tau protein

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