ArticleFrontiers in neuroscience2024
Electroencephalography-based biological and functional characteristics of spinal cord injury patients with neuropathic pain and numbness.
Article in Frontiers in neuroscience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- EEG neurofeedback for the treatment of neuropathic pain in the elderly-a mechanistic review.GeroScience · 2026Review
- The Role of Maladaptive Plasticity in Modulating Pain Pressure Threshold Post-Spinal Cord Injury.Healthcare (Basel, Switzerland) · 2025Article
- The intrinsic reason why complementary tests (clinical neurophysiology, neuroimaging, skin biopsy) cannot establish the diagnosis of neuropathic pain.Frontiers in pain research (Lausanne, Switzerland) · 2025Article
- EEG Oscillations as Neuroplastic Markers of Neural Compensation in Spinal Cord Injury Rehabilitation: The Role of Slow-Frequency Bands.Brain sciences · 2024Article
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Authors and funding
9 authors.
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Abstract
Objectives: To identify potential treatment targets for spinal cord injury (SCI)-related neuropathic pain (NP) by analysing the differences in electroencephalogram (EEG) and brain network connections among SCI patients with NP or numbness. Participants and methods: The EEG signals during rest, as well as left- and right-hand and feet motor imagination (MI), were recorded. The power spectral density (PSD) of the θ (4-8 Hz), α (8-12 Hz), and β (13-30 Hz) bands was calculated by applying Continuous Wavelet Transform (CWT) and Modified S-transform (MST) to the data. We used 21 electrodes as network nodes and performed statistical measurements of the phase synchronisation between two brain regions using a phase-locking value, which captures nonlinear phase synchronisation. Results: The specificity of the MST algorithm was higher than that of the CWT. Widespread non-lateralised event-related synchronization was observed in both groups during the left- and right-hand MI. The PWP (patients with pain) group had lower θ and α bands PSD values in multiple channels of regions including the frontal, premotor, motor, and temporal regions compared with the PWN (patients with numbness) group (all Conclusion: The differences in the power of EEG and network connectivity in the frontal, premotor, motor, and temporal regions are potential biological and functional characteristics that can be used to distinguish NP from numbness. The differences in brain network connections between the two groups suggest that the distinct mechanisms for pain and numbness.
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