Abstract
Stroke remains the leading cause of long-term disability worldwide. Rehabilitation training is essential for motor function recovery following stroke. Specifically, limb linkage rehabilitation training can stimulate motor function in the upper and lower limbs simultaneously. This study aimed to investigate limb linkage rehabilitation task-related changes in cortical activation and effective connectivity (EC) within a functional brain network after stroke by using functional near-infrared spectroscopy (fNIRS) imaging. Thirteen stroke patients with either left hemiparesis (L-H group, n = 6) and or right hemiparesis (R-H group, n = 7) and 16 healthy individuals (control group) participated in this study. A multichannel fNIRS system was used to measure changes in cerebral oxygenated hemoglobin (delta HbO2) and deoxygenated hemoglobin (delta HHb) in the bilateral prefrontal cortices (PFCs), motor cortices (MCs), and occipital lobes (OLs) during (1) the resting state and (2) a motor rehabilitation task with upper and lower limb linkage (first 10 min [task_S1], last 10 min [task_S2]). The frequency-specific EC among the brain regions was calculated based on coupling functions and dynamic Bayesian inference in frequency intervals: high-frequency I (0.6–2 Hz) and II (0.145–0.6 Hz), low-frequency III (0.052–0.145 Hz), and very-low-frequency IV (0.021–0.052 Hz). The results showed that the stroke patients exhibited an asymmetric (greater activation in the contralesional versus ipsilesional motor region) cortical activation pattern versus healthy controls. Compared with the healthy controls, the stroke patients showed significantly lower EC (p < 0.025) in intervals I and II in the resting and task states. The EC from the MC and OL to the right PFC in interval IV was significantly higher in the R-H group than in the control group during the resting and task states (p < 0.025). Furthermore, the L-H group showed significantly higher EC from the MC and OL to the left PFC in intervals III and IV during the task states compared with the control group (p < 0.025). The significantly increased influence of the MC and OL on the contralesional PFC in low- and very-low-frequency bands suggested that plastic reorganization of cognitive resources severed to compensate for impairment in stroke patients during the motor rehabilitation task. This study can serve as a basis for understanding task-related reorganization of functional brain networks and developing novel assessment techniques for stroke rehabilitation.
Highlights
Stroke is a prevalent neurological condition that remains the leading cause of long-term disability worldwide[1,2]
The average value of the delta HbO2 concentration change at the channel midpoint represents its change in the channel region, from which an image is generated by interpolating the inverse distance
These results indicated that the stroke patients exhibited an asymmetric cortical activation pattern compared with healthy controls
Summary
Stroke is a prevalent neurological condition that remains the leading cause of long-term disability worldwide[1,2]. FNIRS is a neuroimaging technique that provides noninvasive detection of relative changes in cerebral oxygenated hemoglobin (delta HbO2) and deoxygenated hemoglobin (delta HHb) at the cortical surface[7] It is an optical imaging method based on hemodynamic responses as an indirect measure of neural activation[8]. Previous studies have demonstrated that the cortical reorganization underlying neurological deficits can be better assessed over entire networks by using a connectivity-based method[23,24] This method can provide insights into the network reorganization of the brain and has important implications for behavior and recovery[25,26,27]. We aimed to investigate motor rehabilitation task with upper and lower limb linkage-related changes in EC patterns within a brain network in stroke patients. This study serves as a basis to understand mechanisms of neural rehabilitation and develop novel assessment techniques for stroke rehabilitation based on cortical fNIRS signals
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