First-in-human prediction of chronic pain state using intracranial neural biomarkers.
Journal
Nature neuroscience
ISSN: 1546-1726
Titre abrégé: Nat Neurosci
Pays: United States
ID NLM: 9809671
Informations de publication
Date de publication:
06 2023
06 2023
Historique:
received:
13
04
2021
accepted:
18
04
2023
medline:
8
6
2023
pubmed:
23
5
2023
entrez:
22
5
2023
Statut:
ppublish
Résumé
Chronic pain syndromes are often refractory to treatment and cause substantial suffering and disability. Pain severity is often measured through subjective report, while objective biomarkers that may guide diagnosis and treatment are lacking. Also, which brain activity underlies chronic pain on clinically relevant timescales, or how this relates to acute pain, remains unclear. Here four individuals with refractory neuropathic pain were implanted with chronic intracranial electrodes in the anterior cingulate cortex and orbitofrontal cortex (OFC). Participants reported pain metrics coincident with ambulatory, direct neural recordings obtained multiple times daily over months. We successfully predicted intraindividual chronic pain severity scores from neural activity with high sensitivity using machine learning methods. Chronic pain decoding relied on sustained power changes from the OFC, which tended to differ from transient patterns of activity associated with acute, evoked pain states during a task. Thus, intracranial OFC signals can be used to predict spontaneous, chronic pain state in patients.
Identifiants
pubmed: 37217725
doi: 10.1038/s41593-023-01338-z
pii: 10.1038/s41593-023-01338-z
pmc: PMC10330878
mid: NIHMS1903355
doi:
Types de publication
Journal Article
Research Support, U.S. Gov't, Non-P.H.S.
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
1090-1099Subventions
Organisme : NINDS NIH HHS
ID : U24 NS113637
Pays : United States
Organisme : NINDS NIH HHS
ID : UH3 NS109556
Pays : United States
Organisme : NINDS NIH HHS
ID : UH3 NS115631
Pays : United States
Informations de copyright
© 2023. The Author(s), under exclusive licence to Springer Nature America, Inc.
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