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Updated: Jun 27, 2026

Functional Near Infrared Spectroscopy of the Sensory and Motor Brain Regions with Simultaneous Kinematic and EMG Monitoring During Motor Tasks
Published on: December 5, 2014
Resting-state brain network alterations in spinal cord injury patients: an fNIRS study
Ying Zou1, Hyeong Seok Lee2, Dae Jung Yang2
1Medical Department, Yueyang Vocational Technical College, Yueyang, Hunan, China.
Objective:
This study focuses on patients with spinal cord injury (SCI), using healthy subjects as controls, and employs functional near-infrared spectroscopy (fNIRS) to compare the strength of resting-state functional connectivity (rsFC) between SCI patients and healthy subjects, providing neuroimaging evidence for the neuropathological mechanisms of sensory-motor dysfunction and other functional impairments in SCI patients.
Method:
Twenty-three healthy adults were included as the health control (HC) group, and 21 SCI patients were included as the SCI group. Data analysis was performed using Nirspark software and SPSS 27.0 to compare the differences in resting-state brain network connectivity between the two groups and to analyze the correlation between brain network connectivity and clinical indicators.
Results:
The SCI group showed significantly reduced interhemispheric SMC connectivity at both HbO₂ and HbR levels (p < 0.05). HbR-based analysis revealed decreased L-PFC ~ R-M1 connectivity (p < 0.01). Interhemispheric SMC connectivity was positively correlated with ASIA sensory and motor scores (p < 0.05), and L-PFC ~ R-M1 connectivity was positively correlated with disease duration (p < 0.001).
Conclusion:
The weakening of interhemispheric SMC connectivity is highly correlated with SCI sensorimotor dysfunction, suggesting it may serve as a potential biomarker for sensorimotor function. Reduced connectivity of PFC-M1 may reflect neural remodeling along common pathways of complex motor function, depression, and neuropathic pain, but this is only a preliminary hypothesis. These quantifiable connectivity features provide potential new targets for monitoring disease progression and evaluating therapeutic interventions, but they need to be further validated in future longitudinal and multimodal studies.
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