Arrow Research search

Author name cluster

Can Tang

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

1 paper
1 author row

Possible papers

1

YNICL Journal 2025 Journal Article

Altered functional connectivity of brainstem ARAS nuclei unveils the mechanisms of disorders of consciousness in sTBI: an exploratory study

  • Peng Zhang
  • Yinan Zhou
  • Haoqi Ni
  • Zhaoneng Huang
  • Can Tang
  • Qichuan Zhuge
  • Lun Dong
  • Jun Zhang

OBJECTIVE: To investigate the functional connectivity (FC) characteristics of Ascending Reticular Activating System (ARAS) in patients with disorders of consciousness (DOC) following severe traumatic brain injury (sTBI), while introducing the Linear support vector machine (LSVM) to predict the recovery of consciousness. METHODS: Resting-state MRI was used to measure FC changes between the brainstem ARAS nuclei and whole-brain voxels. We compared the differences in FC between sTBI patients and healthy controls, as well as between the wake and DOC groups. Furthermore, the LSVM model for consciousness recovery was developed based on the Z-values of regions of interest (ROIs) and/or scale to distinguish the prognosis of sTBI patients. RESULTS: A total of 28 sTBI patients with DOC and 30 healthy controls were included, with no significant baseline differences (p > 0.05). Using the brainstem ARAS nuclei as the ROI, we observed increased FC in the subcortical regions compared to healthy controls. The strength of FC was significantly different between patients who recovered consciousness and those who did not at 6 months post-sTBI (AlphaSim corrected, p 154). Furthermore, the LSVM model demonstrated strong predictive performance, with an area under the receiver operating characteristic curve of 0.81-0.98. CONCLUSIONS: Our study suggest that the disruption FC of ARAS from the subcortex to the cortex may be associated with DOC and prognosis in sTBI patients. Furthermore, the LSVM model shows potential value in distinguishing the recovery of consciousness.