ArticleBrain communications2025
Multi-network dynamical structure of the human brain in the setting of chronic pain: a coordinate-based meta-analysis.
Article in Brain communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Efficacy of transcranial electrical stimulation in the treatment of chronic nonspecific low back pain: a systematic review and meta-analysis.Frontiers in neurology · 2026Pooled it
- Chronic pain and oscillatory neuroplasticity: Review on impaired compensatory network responses in resting-state electroencephalography.Brain network disorders · 2026Article
- Longitudinal co-activation pattern analysis of menstrual cycle-related brain dynamics in primary dysmenorrhea.iScience · 2026Article
- Impaired glymphatic function and advanced brain age gap in chronic migraine: a multimodal MRI study.The journal of headache and pain · 2026Article
- Targeted modulation of thalamocortical and descending control networks in chronic shoulder pain: a longitudinal connectomics study.Frontiers in pain research (Lausanne, Switzerland) · 2026Article
- Anterior insular co-activation patterns associated with stress markers in chronic primary pain.Brain communications · 2026Article
- Convergent structural brain alterations in chronic pain: a multi-metric individual participant data meta-analysis.Brain communications · 2026Article
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Authors and funding
12 authors.
Funding
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Abstract
The treatment of chronic pain represents a widespread clinical challenge. Current approaches to network-based mapping of the cerebral cortex have the potential to localize chronic pain in the brain. In an effort to further characterize the dynamical brain networks, or the 'dynome' in the setting of chronic pain, we performed a Coordinate-Based Meta-Analysis of resting-state functional Magnetic Resonance Imaging studies on chronic pain to create a multinetwork dynome of chronic pain. A cluster-level analysis generated seven statistically significant activation likelihood estimates (ALEs): one for chronic pain as a whole dynome, three for chronic pain conditions, and three for chronic pain mechanisms. Chronic pain is a complex disease process involving tripartite network dysfunction encompassing the Default Mode Network, Central Executive Network and Salience Network. Chronic visceral pain was distinct from chronic headache and chronic musculoskeletal pain, and chronic pain mechanisms have the potential to share common cortical network rearrangements with their respective chronic pain conditions. Collectively, this work represents the first anatomically specific network-based cortical map of chronic pain, with representation of disease-specific and mechanism-specific disruptions in cortical function.
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