ReviewMolecular medicine reports2026
Electroencephalography research in neuropathic pain (Review).
Review in Molecular medicine reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Neuropathic pain (NP), arising from lesions or dysfunction of the somatosensory system, remains a major clinical challenge due to its subjective and multidimensional nature. Traditional pain assessments rely on self‑report scales, which lack objectivity and reproducibility. Electroencephalography (EEG), with its high temporal resolution and accessibility, provides a promising avenue for identifying candidate neurophysiological biomarkers of pain. The current narrative review integrates mechanistic insights and electrophysiological evidence to delineate EEG alterations in NP. Resting‑state θ increases and dominant‑frequency slowing are relatively recurrent in chronic NP, whereas α‑, β‑ and γ‑band findings remain heterogeneous. Network analyses further reveal aberrant prefrontal‑limbic and sensorimotor connectivity, as well as altered cross‑frequency coupling, but the direction and topology of these findings remain dependent on the patient population, recording configuration and analytical metric. Advances in computational EEG analysis, graph theory and machine learning are facilitating exploration of objective, individualized pain assessment frameworks. Emerging portable EEG and multimodal approaches may provide opportunities for future clinical translation. Overall, EEG offers a feasible and dynamic method to bridge subjective pain perception with measurable neurophysiological signatures, paving the way toward precision diagnostics and neuromodulation in NP.
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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.