ArticleFrontiers in neuroscience2026
Pain-side-specific alteration of structural networks in trigeminal neuralgia: a connectome analysis.
Article in Frontiers in neuroscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Objectives: Trigeminal neuralgia (TN) involves disruption in the integrity of the white matter, the side-specific pain topology of these alterations at the network has yet to be defined. In this study, we investigated the lateralization of structural network architecture and nodal characteristics in TN patients. Methods: Whole-brain structural networks (90 × 90 connectivity matrices) were reconstructed from diffusion tensor imaging (DTI) tractography data of 30 TN patients and 20 matched controls. We applied Network-Based Statistics (NBS) to detect altered connectivity sub-networks, and graph theoretical analysis to profile global and nodal properties. Our analysis aimed to delineate changes that were specific to the painful side. Results: NBS analysis revealed that structural connectivity formed subnetworks involving multiple functional networks. A subnetwork involving the anterior cingulate gyrus (ACG) and postcentral gyrus (S1) was identified on the painful side, indicating that TN stimulation may enhance structural connectivity between regions related to salience and somatosensory processing, thereby facilitating the acceleration of pain perception and response. On the non-pain side, we observed enhanced structural connections between visual and attention-related regions. The third subnetwork was characterized by widespread and non-focal reductions in fiber tract connectivity. However, despite these localized alterations, the global network properties of the brain in TN patients remained stable, with node-specific properties undergoing alterations in multiple brain regions, including the cuneus, inferior parietal lobule, and superior frontal gyrus. Conclusion: Herein, we applied NBS and graph theoretical analysis to investigate changes in the structural brain networks of patients with TN. Analysis revealed that specific subnetworks and key nodes can be affected by TN. We also confirmed obvious differences in the involved subnetworks between pain and non-pain sides in TN patients. These findings suggest that these specific subnetworks and nodes could represent valuable biomarkers for clinical evaluation and intervention in TN patients.
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