Background: Robotic-assisted gait training (RAGT) has emerged as a promising strategy to promote neuroplasticity and motor recovery in individuals with spinal cord injury (SCI). This study investigates cortical connectivity during passive robotic gait compared with standing, hypothesizing greater sensor-level network connectivity during gait than during standing.
Methods: Twenty-three individuals with incomplete SCI (ASIA C or D) underwent EEG assessments while performing standing and robotic-assisted gait tasks using the Lokomat system. Graph theory centrality metrics-degree, betweenness, and eigenvector centrality-were applied to identify changes in local integration, hubness, and global node influence across cortical regions.
Results: Cortical connectivity was significantly enhanced during robotic gait compared to standing, particularly in the frontal, central, and sensorimotor regions. Degree centrality increased in frontal (Fz, FC1, FC5) and central (Cz, FC2) regions during gait, indicating stronger local connectivity. Betweenness and eigenvector centrality analyses revealed greater global integration, with Cz emerging as a key hub for network communication.
Discussion: Passive RAGT significantly enhances cortical connectivity, especially in motor-related areas, even without voluntary movement. These findings suggest that passive RAGT is associated with task-related changes in EEG sensor-level network organization in SCI populations. Although these correlation-based connectivity measures do not directly demonstrate cortical engagement or causal neural coupling, the results support the potential of RAGT as a rehabilitation tool and provide further insight into brain network reconfiguration during passive gait.
Keywords: EEG; Functional connectivity; Graph theory; Neuroplasticity; Robotic-assisted gait; Spinal cord injury.
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