Functional neurophysiological biomarkers of early-stage Alzheimer's disease: A perspective of network hyperexcitability in disease progression

Sean Tok*, Abdallah Ahnaou, Wilhelmus Drinkenburg

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

5 Citations (Scopus)
15 Downloads (Pure)

Abstract

Network hyperexcitability (NH) has recently been suggested as a potential neurophysiological biomarker of Alzheimer's disease (AD), as new, more accurate biomarkers of AD are sought. NH has generated interest as a potential biomarker of certain stages in the disease trajectory and even as a disease mechanism by which network dysfunction could be modulated. NH has been demonstrated in several animal models of AD pathology and multiple lines of evidence point to the existence of NH in patients with AD, strongly supporting the physiological and clinical relevance of this indication. Several hypotheses have been put forward to explain the prevalence of NH in animal models through neurophysiological, biochemical, and imaging techniques. However, some of these hypotheses have been built on animal models with limitations and caveats that may have derived NH through other mechanisms or mechanisms without translational validity to sporadic AD patients, potentially leading to an erroneous conclusion of the underlying cause of NH occurring in patients with AD. In this review, we discuss the substantiation for NH in animal models of AD pathology and in human patients, as well as some of the hypotheses considering recently developed animal models that challenge existing hypotheses and mechanisms of NH. In addition, we provide a preclinical perspective on how the development of animal models incorporating AD-specific NH could provide physiologically relevant translational experimental data that may potentially aid the discovery and development of novel therapies for AD.

Original languageEnglish
Pages (from-to)809-836
Number of pages28
JournalJournal of Alzheimer’s Disease
Volume88
Issue number3
Early online date20-Aug-2021
DOIs
Publication statusPublished - 2-Aug-2022

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