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REVIEW article

Front. Neurol.
Sec. Neurotechnology
Volume 15 - 2024 | doi: 10.3389/fneur.2024.1407785
This article is part of the Research Topic Photobiomodulation Therapy for Brain Disorders View all 4 articles

Modifying Alzheimer's Disease Pathophysiology with Photobiomodulation: Model, Evidence, and Future with EEG-guided Intervention

Provisionally accepted
  • Other

The final, formatted version of the article will be published soon.

    This manuscript outlines a model of Alzheimer’s Disease (AD) pathophysiology in progressive layers, from its genesis to the development of biomarkers and then to symptom expression. Genetic predispositions are the major factor that leads to mitochondrial dysfunction and subsequent amyloid and tau protein accumulation, which have been identified as hallmarks of AD. Extending beyond these accumulations, we explore a broader spectrum of pathophysiological aspects, including the blood-brain barrier, blood flow, vascular health, gut-brain microbiodata, glymphatic flow, metabolic syndrome, energy deficit, oxidative stress, calcium overload, inflammation, neuronal and synaptic loss, brain matter atrophy, and reduced growth factors. Photobiomodulation (PBM), which delivers near-infrared light to selected brain regions using portable devices, has been introduced as a therapeutic approach. PBM has the potential to address each of these pathophysiological aspects, with data provided by various studies. They provide mechanistic support for largely small published clinical studies that demonstrate improvements in memory and cognition. They inform of PBM’s potential to treat AD pending validation by large randomized controlled studies. The presentation of brain network and waveform changes on electroencephalography (EEG) provide the opportunity to use these data as a guide for the use of various PBM parameters to improve outcomes. These parameters include wavelength, power density, treatment duration, LED positioning, and pulse frequency. Pulsing at specific frequencies has been found to influence the expression of waveforms and modifications of brain networks. The expression stems from the modulation of cellular and protein structures as revealed in recent studies. These findings provide an EEG-based guide for the use of artificial intelligence to personalize AD treatment through EEG data feedback.

    Keywords: photobiomodulation, Alzheimer's disease, pathophysiology, clinical evidence, clinical studies, EEG, artificial intelligence, Default Mode Network

    Received: 27 Mar 2024; Accepted: 01 Aug 2024.

    Copyright: © 2024 Lim. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.