• Bingyong Xie, Haoyu Ni, Ying Wang, Jiyuan Yao, Zhibin Xu, Kun Zhu, Sicheng Bian, Peiwen Song, Yuanyuan Wu, Yongqiang Yu, and Fulong Dong.
• Department of Orthopedics, The First Affiliated Hospital of Anhui Medical University, Hefei, PR China; Department of Spine Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, PR China.
• World Neurosurg. 2024 Sep 5.

BackgroundDynamic functional network connectivity (dFNC) captures temporal variations in functional connectivity during MRI acquisition. However, the neural mechanisms driving dFNC alterations in the brain networks of patients with Acute incomplete cervical cord injury (AICCI) remain unclear.MethodsThis study included 16 AICCI patients and 16 healthy controls (HC). Initially, Independent Component Analysis (ICA) was employed to extract whole-brain independent components (ICs) from resting-state functional MRI (rs-fMRI) data. Subsequently, a sliding time window approach, combined with k-means clustering, was used to estimate dFNC states for each participant. Finally, a correlation analysis was conducted to examine the association between sensorimotor dysfunction scores in AICCI patients and the temporal characteristics of dFNC.ResultICA was employed to extract 26 whole-brain ICs. Subsequent dynamic analysis identified four distinct connectivity states across the entire cohort. Notably, AICCI patients demonstrated a significant preference for State 3 compared to HC, as evidenced by a higher frequency and longer duration spent in this state. Conversely, State 4 exhibited a reduced frequency and shorter dwell time in AICCI patients. Moreover, correlation analysis revealed a positive association between sensorimotor dysfunction and both the mean dwell time and the fractional of time spent in State 3.ConclusionsPatients with AICCI demonstrate abnormal connectivity within dFNC states, and the temporal characteristics of dFNC are associated with sensorimotor dysfunction scores. These findings highlight the potential of dFNC as a sensitive biomarker for detecting network functional changes in AICCI patients, providing valuable insights into the dynamic alterations in brain connectivity related to sensorimotor dysfunction in this population.Copyright © 2024 Elsevier Inc. All rights reserved.

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