Resting-state electroencephalography (EEG) biomarkers of chronic neuropathic pain. A systematic review.

Biomarker Chronic pain Diagnosis Human Neurofeedback Neuropathic pain Non-invasive brain stimulation Quantitative EEG

Journal

NeuroImage
ISSN: 1095-9572
Titre abrégé: Neuroimage
Pays: United States
ID NLM: 9215515

Informations de publication

Date de publication:
09 2022
Historique:
received: 07 03 2022
revised: 09 05 2022
accepted: 31 05 2022
pubmed: 7 6 2022
medline: 14 7 2022
entrez: 6 6 2022
Statut: ppublish

Résumé

Diagnosis and management of chronic neuropathic pain are challenging, leading to current efforts to characterize 'objective' biomarkers of pain using imaging or neurophysiological techniques, such as electroencephalography (EEG). A systematic literature review was conducted in PubMed-Medline and Web-of-Science until October 2021 to identify EEG biomarkers of chronic neuropathic pain in humans. The risk of bias was assessed by the Newcastle-Ottawa-Scale. Experimental, provoked, or chronic non-neuropathic pain studies were excluded. We identified 14 studies, in which resting-state EEG spectral analysis was compared between patients with pain related to a neurological disease and patients with the same disease but without pain or healthy controls. From these heterogeneous exploratory studies, some conclusions can be drawn, even if they must be weighted by the fact that confounding factors, such as medication and association with anxio-depressive disorders, are generally not taken into account. Overall, EEG signal power was increased in the θ band (4-7Hz) and possibly in the high-β band (20-30Hz), but decreased in the high-α-low-β band (10-20Hz) in the presence of ongoing neuropathic pain, while increased γ band oscillations were not evidenced, unlike in experimental pain. Consequently, the dominant peak frequency was decreased in the θ-α band and increased in the whole-β band in neuropathic pain patients. Disappointingly, pain intensity correlated with various EEG changes across studies, with no consistent trend. This review also discusses the location of regional pain-related EEG changes in the pain connectome, as the perspectives offered by advanced techniques of EEG signal analysis (source location, connectivity, or classification methods based on artificial intelligence). The biomarkers provided by resting-state EEG are of particular interest for optimizing the treatment of chronic neuropathic pain by neuromodulation techniques, such as transcranial alternating current stimulation or neurofeedback procedures.

Identifiants

pubmed: 35659993
pii: S1053-8119(22)00470-0
doi: 10.1016/j.neuroimage.2022.119351
pii:
doi:

Substances chimiques

Biomarkers 0

Types de publication

Journal Article Review Systematic Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

119351

Informations de copyright

Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest None.

Auteurs

Thibaut Mussigmann (T)

Univ Paris Est Creteil, EA4391, ENT, Créteil, France; Clinical Neurophysiology Unit, Henri Mondor Hospital, AP-HP, Créteil, France.

Benjamin Bardel (B)

Univ Paris Est Creteil, EA4391, ENT, Créteil, France; Clinical Neurophysiology Unit, Henri Mondor Hospital, AP-HP, Créteil, France.

Jean-Pascal Lefaucheur (JP)

Univ Paris Est Creteil, EA4391, ENT, Créteil, France; Clinical Neurophysiology Unit, Henri Mondor Hospital, AP-HP, Créteil, France. Electronic address: jean-pascal.lefaucheur@hmn.aphp.fr.

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Classifications MeSH