Literature DB >> 24933720

Increased reward in ankle robotics training enhances motor control and cortical efficiency in stroke.

Ronald N Goodman1, Jeremy C Rietschel, Anindo Roy, Brian C Jung, Jason Diaz, Richard F Macko, Larry W Forrester.   

Abstract

Robotics is rapidly emerging as a viable approach to enhance motor recovery after disabling stroke. Current principles of cognitive motor learning recognize a positive relationship between reward and motor learning. Yet no prior studies have established explicitly whether reward improves the rate or efficacy of robotics-assisted rehabilitation or produces neurophysiologic adaptations associated with motor learning. We conducted a 3 wk, 9-session clinical pilot with 10 people with chronic hemiparetic stroke, randomly assigned to train with an impedance-controlled ankle robot (anklebot) under either high reward (HR) or low reward conditions. The 1 h training sessions entailed playing a seated video game by moving the paretic ankle to hit moving onscreen targets with the anklebot only providing assistance as needed. Assessments included paretic ankle motor control, learning curves, electroencephalograpy (EEG) coherence and spectral power during unassisted trials, and gait function. While both groups exhibited changes in EEG, the HR group had faster learning curves (p = 0.05), smoother movements (p </= 0.05), reduced contralesional-frontoparietal coherence (p </= 0.05), and reduced left-temporal spectral power (p </= 0.05). Gait analyses revealed an increase in nonparetic step length (p = 0.05) in the HR group only. These results suggest that combining explicit rewards with novel anklebot training may accelerate motor learning for restoring mobility.

Entities:  

Keywords:  EEG; EEG coherence; EEG spectral zzm321990power; ankle robotics; anklebot; chronic hemiparetic stroke; cognitive motor learning; gait; plasticity; reward

Mesh:

Year:  2014        PMID: 24933720     DOI: 10.1682/JRRD.2013.02.0050

Source DB:  PubMed          Journal:  J Rehabil Res Dev        ISSN: 0748-7711


  18 in total

1.  Robotic Assistance for Training Finger Movement Using a Hebbian Model: A Randomized Controlled Trial.

Authors:  Justin B Rowe; Vicky Chan; Morgan L Ingemanson; Steven C Cramer; Eric T Wolbrecht; David J Reinkensmeyer
Journal:  Neurorehabil Neural Repair       Date:  2017-08       Impact factor: 3.919

2.  Intimacy motivations and pre-exposure prophylaxis (PrEP) adoption intentions among HIV-negative men who have sex with men (MSM) in romantic relationships.

Authors:  Kristi E Gamarel; Sarit A Golub
Journal:  Ann Behav Med       Date:  2015-04

3.  Reward-Based Improvements in Motor Control Are Driven by Multiple Error-Reducing Mechanisms.

Authors:  Olivier Codol; Peter J Holland; Sanjay G Manohar; Joseph M Galea
Journal:  J Neurosci       Date:  2020-03-31       Impact factor: 6.167

4.  Contribution of explicit processes to reinforcement-based motor learning.

Authors:  Peter Holland; Olivier Codol; Joseph M Galea
Journal:  J Neurophysiol       Date:  2018-03-14       Impact factor: 2.714

5.  Visuomotor errors drive step length and step time adaptation during 'virtual' split-belt walking: the effects of reinforcement feedback.

Authors:  Sumire Sato; Ashley Cui; Julia T Choi
Journal:  Exp Brain Res       Date:  2021-11-23       Impact factor: 1.972

Review 6.  Electromechanical-assisted training for walking after stroke.

Authors:  Jan Mehrholz; Simone Thomas; Cordula Werner; Joachim Kugler; Marcus Pohl; Bernhard Elsner
Journal:  Cochrane Database Syst Rev       Date:  2017-05-10

Review 7.  Non-invasive brain stimulation: an interventional tool for enhancing behavioral training after stroke.

Authors:  Maximilian J Wessel; Máximo Zimerman; Friedhelm C Hummel
Journal:  Front Hum Neurosci       Date:  2015-05-15       Impact factor: 3.169

8.  Design and Optimization of an EEG-Based Brain Machine Interface (BMI) to an Upper-Limb Exoskeleton for Stroke Survivors.

Authors:  Nikunj A Bhagat; Anusha Venkatakrishnan; Berdakh Abibullaev; Edward J Artz; Nuray Yozbatiran; Amy A Blank; James French; Christof Karmonik; Robert G Grossman; Marcia K O'Malley; Gerard E Francisco; Jose L Contreras-Vidal
Journal:  Front Neurosci       Date:  2016-03-31       Impact factor: 4.677

Review 9.  Combining Upper Limb Robotic Rehabilitation with Other Therapeutic Approaches after Stroke: Current Status, Rationale, and Challenges.

Authors:  Stefano Mazzoleni; Christophe Duret; Anne Gaëlle Grosmaire; Elena Battini
Journal:  Biomed Res Int       Date:  2017-09-13       Impact factor: 3.411

10.  A Feasibility Study of SSVEP-Based Passive Training on an Ankle Rehabilitation Robot.

Authors:  Xiangfeng Zeng; Guoli Zhu; Lan Yue; Mingming Zhang; Shane Xie
Journal:  J Healthc Eng       Date:  2017-09-17       Impact factor: 2.682

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