Saturday, September 15, 2018

Differentiated effects of robot hand training with and without neural guidance on neuroplasticity patterns in chronic stroke

Whatever the hell neural guidance is? Might and could are used instead of does and will, so further followup research will be needed to create protocols.
https://www.frontiersin.org/articles/10.3389/fneur.2018.00810/abstract
 Xin Wang1,  Wan-wa Wong1, Rui Sun1, Winnie C. Chu2 and  Raymond K. Tong1, 3*
  • 1The Chinese University of Hong Kong, Hong Kong
  • 2Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, China
  • 3Brain and Mind Institute, The Chinese University of Hong Kong, China
Robot-assisted training combined with neural guided strategy has been increasingly applied to stroke rehabilitation. However, the induced neuroplasticity is seldom characterized. It is still uncertain whether this kind of guidance could enhance the long-term training effect for stroke motor recovery. This study was conducted to explore the clinical improvement and the neurological changes after 20-session guided or non-guided robot hand training using two measures: changes in brain discriminant ability between motor-imagery and resting states revealed from electroencephalography(EEG) signals and changes in brain network variability revealed from resting-state functional magnetic resonance imaging(fMRI) data in twenty-four chronic stroke subjects. The subjects were randomly assigned to receive either combined action observation(AO) with EEG-guided robot-hand training(RobotEEG_AO, n=13) or robot-hand training without AO and EEG guidance(Robotnon-EEG_Text, n=11). The robot hand in RobotEEG_AO group was activated only when significant mu suppression(8-12Hz) was detected from subjects’ EEG signals in ipsilesional hemisphere, while the robot hand in Robotnon-EEG_Text group was randomly activated regardless of their EEG signals. Paretic upper-limb motor functions were evaluated at three time-points: before, immediately after and 6 months after the interventions. Only RobotEEG_AO group showed a long-term significant improvement in their upper-limb motor functions while no significant and long-lasting training effect on the paretic motor functions was shown in Robotnon-EEG_Text group. Significant neuroplasticity changes were only observed in RobotEEG_AO group as well. The brain discriminant ability based on the ipsilesional EEG signals significantly improved after intervention. For brain network variability, the whole brain was first divided into six functional subnetworks, and significant increase in the temporal variability was found in four out of the six subnetworks, including sensory-motor areas, attention network, auditory network and default mode network after intervention. Our results revealed the differences in the long-term training effect and the neuroplasticity changes following the two interventional strategies: with and without neural guidance. The findings might imply that sustainable motor function improvement could be achieved through proper neural guidance, which might provide insights into strategies for effective stroke rehabilitation. Furthermore, neuroplasticity could be promoted more profoundly by the intervention with proper neurofeedback, and might be shaped in relation to better motor skill acquisition.
Keywords: long-term training effect, Motor Imagery, EEG discriminant rate, resting state fMRI, Temporal variability, brain network, action observation, motor recovery
Received: 16 May 2018; Accepted: 07 Sep 2018.
Edited by:
Valerie M. Pomeroy, University of East Anglia, United Kingdom
Reviewed by:
Bernhard Sehm, Max-Planck-Institut für Kognitions- und Neurowissenschaften, Germany
Sheng Li, University of Texas Health Science Center at Houston, United States  
Copyright: © 2018 Wang, Wong, Sun, Chu and Tong. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Prof. Raymond K. Tong, The Chinese University of Hong Kong, Shatin, Hong Kong, kytong@cuhk.edu.hk

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