Previous studies have found structural and functional abnormalities in brain structures in Trigeminal Neuralgia (TN) patients compared to healthy controls. Studies have also examined aberrations in brain networks in TN patients. This is the first study to investigate causal interactions in brain networks and relate these interactions to the level of TN pain. The aim was to gain a deeper understanding of the central mechanisms of TN pain, with a particular focus being placed on how causal interactions in brain networks give rise to TN pain generation and perception. The hope is that this data will enable researchers to better target areas of the brain that regulate the pain of Trigeminal Neuralgia

Functional MRI (fMRI) data was gathered from 39 typical (TN1) patients when they rested quietly in the scanner, and a second set of scans was made while the patients in the scanner continuously recorded their pain levels using a tracking ball. Granger causality was used to analyze the data and 5 causal interactions where identified that were consistently associated with the level of pain experienced by patients.

  • Thalamus——————Dorsal Anterior cingulate cortex (dACC)
  • Caudate——————–Inferior temporal gyrus
  • Precentral gyrus———-Inferior temporal gyrus
  • Supramarginal gyrus—-Inferior temporal gyrus
  • Bankssts——————-Inferior temporal gyrus

It should be noted that four causal interactions, stemming from four different source regions share the same target region, the inferior temporal gyrus (ITG). Other research has shown that abnormal activity in the ITG may play a role in the mechanism of TN pain. This study is consistent with the finding that TN may impact the function of the ITG and identified the ITG as a crucial target area for causal influences from other brain structures.

Using these 5 causal interactions to predict the patients pain score, the model was able to explain approximately 36% of the variance in pain levels. A model trained on these 5 causal interactions and actual pain values from one scanning session, was able to predict what the pain levels would be in a second scanning session using just the causal interaction values from the second session, cross-validating the models.

Previous studies on pain processing have identified two ascending pain-supporting pathways and one pain inhibiting descending pathway. The thalamus as part of both ascending pathways, receives nociceptive input from the periphery, processes the information and transmits the information to the dACC. The magnitude of pain-evoked activation in the dACC is deemed crucial in determining an individual’s response to pain. The dACC also modulates pain perception as part of the pain-inhibiting descending pathway. In this study the causal influence from the thalamus to the dACC was positively associated with the level of pain. The causal influence in the reverse direction, dACC to thalamus was not found to be predictive of pain levels. This suggests that the dACC may not play a role in the downregulation of thalamic activity in TN pain as it does in other pain conditions.

These results obtained by applying novel analytical methods to neuroimaging data provide important insights into the pathophysiology of TN and could inform future studies.

This study conducted by Yun Liang, Qing Zhao, John Neubert and Mingzhou Ding of the University of Florida, was funded by a grant from the Facial Pain Research Foundation.

Liang Y, Zhao Q, Neubert JK, Ding M. Causal interactions in brain networks predict pain levels in trigeminal neuralgia. Brain Res Bull. 2024 Jun 1;211:110947. doi: 10.1016/j.brainresbull.2024.110947. Epub 2024 Apr 12. PMID: 38614409.