TY - JOUR
T1 - Changes in electroencephalography complexity and functional magnetic resonance imaging connectivity following robotic hand training in chronic stroke
AU - Khan, Ahsan
AU - Chen, Cheng
AU - Yuan, Kai
AU - Wang, Xin
AU - Mehra, Prabhav
AU - Liu, Yunmeng
AU - Tong, Raymond Kai Yu
N1 - This study is supported by Hong Kong Research Grant Council (GRF No: 14208118), Hong Kong.
Publisher Copyright:
© 2020 Taylor & Francis Group, LLC.
PY - 2021/10
Y1 - 2021/10
N2 - Introduction: In recent years, robotic training has been utilized for recovery of motor control in patients with motor deficits. Along with clinical assessment, electrical patterns in the brain have emerged as a marker for studying changes in the brain associated with brain injury and rehabilitation. These changes mainly involve an imbalance between the two hemispheres. We aimed to study the effect of brain computer interface (BCI)-based robotic hand training on stroke subjects using clinical assessment, electroencephalographic (EEG) complexity analysis, and functional magnetic resonance imaging (fMRI) connectivity analysis.Method: Resting-state simultaneous EEG-fMRI was conducted on 14 stroke subjects before and after training who underwent 20 sessions robot hand training. Fractal dimension (FD) analysis was used to assess neuronal impairment and functional recovery using the EEG data, and fMRI connectivity analysis was performed to assess changes in the connectivity of brain networks.Results: FD results indicated a significant asymmetric difference between the ipsilesional and contralesional hemispheres before training, which was reduced after robotic hand training. Moreover, a positive correlation between interhemispheric asymmetry change for central brain region and change in Fugl Meyer Assessment (FMA) scores for upper limb was observed. Connectivity results showed a significant difference between pre-training interhemispheric connectivity and post-training interhemispheric connectivity. Moreover, the change in connectivity correlated with the change in FMA scores. Results also indicated a correlation between the increase in connectivity for motor regions and decrease in FD interhemispheric asymmetry for central brain region covering the motor area.Conclusion: In conclusion, robotic hand training significantly facilitated stroke motor recovery, and FD, along with connectivity analysis can detect neuroplasticity changes.
AB - Introduction: In recent years, robotic training has been utilized for recovery of motor control in patients with motor deficits. Along with clinical assessment, electrical patterns in the brain have emerged as a marker for studying changes in the brain associated with brain injury and rehabilitation. These changes mainly involve an imbalance between the two hemispheres. We aimed to study the effect of brain computer interface (BCI)-based robotic hand training on stroke subjects using clinical assessment, electroencephalographic (EEG) complexity analysis, and functional magnetic resonance imaging (fMRI) connectivity analysis.Method: Resting-state simultaneous EEG-fMRI was conducted on 14 stroke subjects before and after training who underwent 20 sessions robot hand training. Fractal dimension (FD) analysis was used to assess neuronal impairment and functional recovery using the EEG data, and fMRI connectivity analysis was performed to assess changes in the connectivity of brain networks.Results: FD results indicated a significant asymmetric difference between the ipsilesional and contralesional hemispheres before training, which was reduced after robotic hand training. Moreover, a positive correlation between interhemispheric asymmetry change for central brain region and change in Fugl Meyer Assessment (FMA) scores for upper limb was observed. Connectivity results showed a significant difference between pre-training interhemispheric connectivity and post-training interhemispheric connectivity. Moreover, the change in connectivity correlated with the change in FMA scores. Results also indicated a correlation between the increase in connectivity for motor regions and decrease in FD interhemispheric asymmetry for central brain region covering the motor area.Conclusion: In conclusion, robotic hand training significantly facilitated stroke motor recovery, and FD, along with connectivity analysis can detect neuroplasticity changes.
KW - connectivity analysis
KW - Electroencephalography (EEG)
KW - fractal analysis
KW - Functional Magnetic Resonance Imaging (fMRI)
KW - stroke rehabilitation
UR - http://www.scopus.com/inward/record.url?scp=85089504741&partnerID=8YFLogxK
UR - https://www.tandfonline.com/doi/full/10.1080/10749357.2020.1803584
U2 - 10.1080/10749357.2020.1803584
DO - 10.1080/10749357.2020.1803584
M3 - Journal article
C2 - 32799771
AN - SCOPUS:85089504741
SN - 1074-9357
VL - 28
SP - 276
EP - 288
JO - Topics in Stroke Rehabilitation
JF - Topics in Stroke Rehabilitation
IS - 4
ER -
