Modular organization of brain resting state networks in patients with classical trigeminal neuralgia

Yuan Hsiung Tsai, Xia Liang, Jen Tsung Yang, Li Ming Hsu*

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

10 Scopus citations


Background: The modular organization of brain networks in trigeminal neuralgia patients has remained largely unknown. We aimed to analyze the brain modules and intermodule connectivity in patients with trigeminal neuralgia before and after percutaneous radiofrequency rhizotomy treatment to identify specific modules that may be associated with the development and brain plasticity of trigeminal neuralgia and to test the ability of modularity analysis to be a predictive imaging biomarker for the treatment effect in patients with trigeminal neuralgia. Methods: A total of 25 patients with right trigeminal neuralgia and 20 matched healthy subjects were included. Blood-oxygen-level dependent resting state fMRI was used to analyze the brain modular organization. Results: Whole brain modularity analysis identified seven modules. The metric of intermodule connectivity, participation coefficient, of the sensorimotor network and default mode network modules were significantly lower in patients and increased after surgery. The participation coefficient of the subcortical modules was associated with the pain duration. Higher communication between the default mode network module and other modules before surgery was associated with a better treatment response. Furthermore, the subcortical module was a significant contributor to the participation coefficient relationship of the default mode network module with the treatment response, and the bilateral midcingulate cortex and thalamus were major connectors in the subcortical module. Conclusions: These findings have important implications regarding the global brain modular responses to chronic neuropathic pain and it may be feasible to use the modularity analysis as part of a risk stratification to predict the treatment response.

Original languageEnglish
Article number102027
JournalNeuroImage: Clinical
StatePublished - 2019
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2019 The Author(s)


  • Functional MRI
  • Modular organization
  • Pain chronification
  • Radiofrequency rhizotomy
  • Trigeminal neuralgia


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