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Author Spotlight: Methodologies and Advancements of Chronic Pain Management Research
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Exploring electroencephalographic chronic pain biomarkers: a mega-analysis.

Felix S Bott1, Paul Theo Zebhauser1, Vanessa D Hohn2

  • 1Department of Neurology, School of Medicine and Health, Technical University of Munich (TUM), Munich, Germany; TUM-Neuroimaging Center, School of Medicine and Health, TUM, Munich, Germany; Center for Interdisciplinary Pain Medicine, School of Medicine and Health, TUM, Munich, Germany.

Ebiomedicine
|October 1, 2025
PubMed
Summary

Chronic pain alters brain function, but brain-based biomarkers require further development. This study found robust associations between pain intensity and brain network connectivity using electroencephalography (EEG).

Keywords:
BiomarkersChronic painElectroencephalographyLarge-scale brain networksReplicability

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Area of Science:

  • Neuroscience
  • Biomarkers
  • Chronic Pain Research

Background:

  • Chronic pain is linked to brain function alterations.
  • These changes may serve as brain-based biomarkers for diagnosis and treatment.
  • Developing reliable biomarkers is crucial for managing chronic pain.

Purpose of the Study:

  • To investigate associations between chronic pain and large-scale brain network function.
  • To identify potential electroencephalography (EEG)-based biomarkers for chronic pain.

Main Methods:

  • Analysis of resting-state EEG data from 614 individuals with chronic pain.
  • Utilized a discovery-replication approach and mega-analysis.
  • Employed multivariate analyses to identify connectivity patterns across frequencies.

Main Results:

  • Limited replicability for pain intensity and brain network connectivity associations.
  • Robust associations found between pain intensity and theta frequency network connectivity, including the limbic network.
  • Multivariate analyses revealed connectivity patterns across theta, alpha, and beta frequencies associated with pain intensity.

Conclusions:

  • EEG-based biomarkers for chronic pain present challenges but show promise.
  • Findings guide the development of scalable and affordable EEG biomarkers.
  • Further research is needed to refine EEG-based chronic pain assessment.