ArticlePain2019
Brain dysfunction in chronic pain patients assessed by resting-state electroencephalography.
Article in Pain, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 69 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
69 citing papers in PubMed, 2 syntheses or guidelines pooled it, 127 citations in OpenAlex.
- Brain network properties in chronic pain-a systematic review and meta-analysis of graph-based connectivity metrics.Frontiers in neuroscience · 2025Pooled it
- A meta-analysis of neuroimaging evidence for acupuncture-mediated modulation of altered central pain processing in patients with chronic pain.Frontiers in neurologyPooled it
- Decreased neural inhibitory state in fibromyalgia pain: A cross-sectional study.Neurophysiologie clinique = Clinical neurophysiology · 2020Trial
- Electroencephalography research in neuropathic pain (Review).Molecular medicine reports · 2026Review
- Chronic pain and oscillatory neuroplasticity: Review on impaired compensatory network responses in resting-state electroencephalography.Brain network disorders · 2026Article
- EEG-based clustering shows distinct separation of chronic pain patients before spinal cord stimulation surgery.NeuroImage · 2026Article
- EEG Neurofeedback for Major Depressive Disorder: A Scoping Review.Alpha psychiatry · 2026Review
- Individual differences in the empathic experience of pain: An EEG and machine learning approach.Cognitive, affective & behavioral neuroscience · 2026Article
- Trust-gated synthetic EEG augmentation reduces performance drops when generalizing to new patients.NPJ digital medicine · 2026Article
- Machine learning-based identification of abnormal functional connectivity in obesity across different metabolic states.Communications medicine · 2026Article
- Pulsed Radiofrequency Analgesia Alters EEG Spatiotemporal Dynamics: A Microstate-Based Exploratory Study.Pain and therapy · 2026Article
- Neuroimaging-Guided Insights into the Molecular and Network Mechanisms of Chronic Pain and Neuromodulation.International journal of molecular sciences · 2026Review
- Beyond device parameters: psychological predictors of spinal cord stimulation success and their neurobiological mechanisms-a narrative review.Frontiers in psychology · 2026Review
- Exploratory EEG correlates of sensory and affective pain dimensions in patients with chronic widespread pain.Frontiers in pain research (Lausanne, Switzerland) · 2026Article
- Effects of nocturnal melatonin-based tissue-bone homeostasis manipulation at varying time points on pain and central mechanisms in individuals with knee osteoarthritis: a randomized controlled trial.Frontiers in bioengineering and biotechnology · 2026Article
- Quantitative electroencephalography as a next-generation tool in neurodiagnostics: significance, clinical applications, and practical interpretative frameworks.Frontiers in neuroscience · 2026Review
- EEG Spectral Analysis in Chronic Pain During Rest and Cognitive Reasoning.Sensors (Basel, Switzerland) · 2025Article
- Multimodal hypersensitivity and somatic symptoms predict adolescent postmenarchal widespread pain.Pain · 2025Article
- Exploring electroencephalographic chronic pain biomarkers: a mega-analysis.EBioMedicine · 2025Article
- Machine learning classification of active viewing of pain and non-pain images using EEG does not exceed chance in external validation samples.Cognitive, affective & behavioral neuroscience · 2025Article
9 more citing papers are in PubMed but not listed here.
Corrections and comments
- Erratum issued
Authors and funding
12 authors at 3 institutions in 2 countries.
Funding
Abstract
Chronic pain is a common and severely disabling disease whose treatment is often unsatisfactory. Insights into the brain mechanisms of chronic pain promise to advance the understanding of the underlying pathophysiology and might help to develop disease markers and novel treatments. Here, we systematically exploited the potential of electroencephalography to determine abnormalities of brain function during the resting state in chronic pain. To this end, we performed state-of-the-art analyses of oscillatory brain activity, brain connectivity, and brain networks in 101 patients of either sex suffering from chronic pain. The results show that global and local measures of brain activity did not differ between chronic pain patients and a healthy control group. However, we observed significantly increased connectivity at theta (4-8 Hz) and gamma (>60 Hz) frequencies in frontal brain areas as well as global network reorganization at gamma frequencies in chronic pain patients. Furthermore, a machine learning algorithm could differentiate between patients and healthy controls with an above-chance accuracy of 57%, mostly based on frontal connectivity. These results suggest that increased theta and gamma synchrony in frontal brain areas are involved in the pathophysiology of chronic pain. Although substantial challenges concerning the reproducibility of the findings and the accuracy, specificity, and validity of potential electroencephalography-based disease markers remain to be overcome, our study indicates that abnormal frontal synchrony at theta and gamma frequencies might be promising targets for noninvasive brain stimulation and/or neurofeedback approaches.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.