Scope and Rationale
The field of neuromodulation is undergoing rapid transformation, offering renewed hope for individuals suffering from chronic pain. Central to this evolution is the discovery and implementation of biomarkers—biological, physiological, and behavioral indicators capable of guiding and optimizing neuromodulatory interventions targeting both the brain and spinal cord. Biomarkers derived from neuroimaging, neurophysiology, molecular profiling, and innovative digital health technologies hold the promise of enhancing precision, efficacy, and personalization in pain management.
This Research Topic aims to consolidate cutting-edge research and comprehensive reviews addressing the identification, validation, and clinical application of biomarkers in neuromodulation for pain. By integrating insights from brain, spinal cord, and behavioral studies, we seek to explore how biomarkers can predict treatment outcomes, inform mechanisms of action, and enable adaptive, closed-loop neuromodulatory strategies.

Key Themes and Areas of Interest

1. Imaging Biomarkers
- Advanced neuroimaging (e.g., fMRI, PET, DTI) to identify biomarkers linked to neuromodulatory efficacy and pain relief.
- Structural and functional brain and spinal cord changes pre- and post-neuromodulation.
2. Neurophysiological and Behavioral Biomarkers
- EEG, EMG, evoked potentials, and other electrophysiological signatures of pain modulation and treatment responsiveness.
- Behavioral and digital phenotyping for real-time monitoring of pain states and neuromodulation outcomes.
3. Molecular and Genetic Biomarkers
- Genetic markers, inflammatory mediators, neurotransmitters, and cytokines associated with individual responses to neuromodulation.
- Molecular pathways linking biomarker profiles to therapeutic mechanisms.
4. Predictive, Prognostic, and Mechanistic Insights
- Biomarkers predicting patient stratification, treatment responsiveness, and long-term outcomes.
- Longitudinal and translational studies linking biomarkers to mechanisms of action in both preclinical and clinical settings.
5. Machine Learning, AI, and Data Integration
- Artificial intelligence and machine learning models for biomarker discovery, outcome prediction, and patient stratification.
- Multimodal data integration (imaging, physiology, behavior) for precision neuromodulation.
6. Wearable, Implantable, and Continuous Monitoring Technologies
- Development of wearable or implantable devices for real-time biomarker tracking and feedback.
- Digital health innovations enabling continuous assessment of pain and adaptive therapy adjustment.
7. Adaptive and Closed-Loop Neuromodulation
- Clinical validation of closed-loop neuromodulation systems guided by biomarker feedback.
- Real-world applications and case studies demonstrating personalized, dynamic treatment paradigms.
8. Translational and Interdisciplinary Approaches
- Bridging preclinical research with clinical implementation to elucidate mechanisms and improve therapeutic outcomes.
- Ethical, regulatory, and practical challenges in biomarker-driven neuromodulation.
- Cross-disciplinary collaborations across neuroscience, engineering, bioinformatics, and clinical practice.

Article Types Welcomed
We encourage submissions across a wide spectrum of scientific contributions, including:
- Original Research
- Systematic Reviews and Meta-Analyses
- Methodological and Technical Reports
- Perspectives and Opinion Articles
- Case Studies and Clinical Trials

Goal of the Collection
This collection seeks to drive the next generation of biomarker-informed neuromodulation, advancing the field toward truly personalized pain therapeutics. By uniting basic science, engineering innovation, and clinical application, we aim to shape the future of adaptive, precise, and mechanistically grounded interventions for chronic pain

Are you interested in contributing a manuscript to this Research Topic?

Biomarkers and Adaptive Neuromodulation in Pain: From Mechanisms to Precision Therapies