ReviewGeroScience2026
EEG neurofeedback for the treatment of neuropathic pain in the elderly-a mechanistic review.
Review in GeroScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
6 citing papers in PubMed.
- Chronic pain and oscillatory neuroplasticity: Review on impaired compensatory network responses in resting-state electroencephalography.Brain network disorders · 2026Article
- Review
- Efficient Blended Models for Analysis and Detection of Neuropathic Pain from EEG Signals Using Machine Learning.Bioengineering (Basel, Switzerland) · 2026Article
- Quantitative electroencephalography as a next-generation tool in neurodiagnostics: significance, clinical applications, and practical interpretative frameworks.Frontiers in neuroscience · 2026Review
- Review
- Exploratory quantitative EEG characteristics in children with autism spectrum disorder.Frontiers in psychiatry · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Neuropathic pain (NP) is a complex pain disorder that constitutes a significant problem in the aging population, impacting quality of life and everyday functioning. In the quest to develop effective treatments, much research effort has been made to understand brain activity in people with NP, revealing a number of disordered electroencephalogram (EEG) patterns. This information can then be used to inform neurofeedback therapy, a novel approach that involves volitionally training brain activity in a closed loop. In this review of the existent literature we had three main objectives: (1) to summarize the reported EEG signatures of NP, (2) to evaluate the therapeutic efficacy of neurofeedback in the treatment of NP, and (3) to present the potential mechanisms of neurofeedback action in NP. Consequently, literature searches were conducted on the PubMed/Medline, Research Gate, and Cochrane databases. We identified 18 studies that examined resting-state EEG patterns in NP, and seven studies that investigated EEG-based neurofeedback in NP. Most biomarker studies of NP showed typical EEG patterns consisting of excess theta activity and decreased alpha activity. Neurofeedback study outcomes were largely promising in terms of treatment efficacy, but their quality was low. In turn, based on these results, we proposed hypothesis-based neurofeedback protocols and discussed the potential mechanisms of neurofeedback in the treatment of NP, including why this treatment option may be beneficial in the elderly population. Neurofeedback is a promising treatment option for NP, but caution should be exercised in interpreting the results due to the low number and methodological quality of research studies. A larger body of research studies points to common patterns of EEG abnormality in NP, which could be directly targeted with neurofeedback. The main advantage of this therapeutic approach is that it has no side effects and may be considered a valuable form of treatment in more frail populations such as the elderly.
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What OpenQuestion holds
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.