RT - Journal of Oral & Facial Pain and Headache ID - 10.22514/jofph.2026.006 T1 - Investigating changes of functional brain networks in painful temporomandibular disorders: a resting-state fMRI study A1 - Yujiao Jiang A1 - Xin Li A1 - Mengqi Liu A1 - Zhiye Chen K1 - Temporomandibular disorders; Pain; Resting-state fMRI; Brain networks; Clustering coefficient; Local efficiency YR - 2026 SP - 61 AB -

Background: Temporomandibular disorders (TMD), particularly pain-related TMD (TMDp), are closely associated with social and psychological factors. However, the neuromechanisms of pain of TMDp are still currently unclear. This study aimed to investigate the altered topological properties of the brain network in the TMDp patients using resting-state functional magnetic resonance imaging (rs-fMRI), and to explore the association between these parameters and emotional and clinical variables of TMDp. Methods: A total of 41 TMDp patients and 33 age- and gender-matched healthy controls (NCs) were recruited, and rs-fMRI data were obtained from a 3.0T MR scanner. The topological properties of brain functional networks were calculated based on the rs-fMRI data and were compared between two groups to investigate the altered topological characteristics in TMDp. The correlation analysis was also performed between the abnormal topological characteristics and the clinical variables in TMDp patients. Results: TMDp patients presented significantly decreased clustering coefficient (Cp) and decreased local efficiency (Eloc) when sparsity threshold was 0.05 and 0.06 compared with NCs (p < 0.05), and the Eloc values when sparsity threshold was 0.06 were positively correlated with depressive (r = 0.319, p = 0.042) and anxious (r = 0.348, p = 0.026) variables in TMDp patients. Conclusions: The current study demonstrated the abnormal topological changes of the brain network were observed in TMDp, which could be helpful in understanding the neuromechanisms of pain of TMDp. The topological properties of the brain network based on rs-fMRI could be considered as a new simple tool to monitor the dysfunction network of the brain in TMDp.