title: Increased reward in ankle robotics training enhances motor control and cortical efficiency in stroke.
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.
authors.affiliation: Baltimore VAMC Annex, Maryland Exercise and Robotics Center of Excellence, 209 W. Fayette St, Rm 207, Baltimore, MD 21201. Ronald.Goodman@va.gov.
authors.forename: Ronald N
authors.initials: RN
authors.lastname: Goodman
authors.forename: Jeremy C
authors.initials: JC
authors.lastname: Rietschel
authors.forename: Anindo
authors.initials: A
authors.lastname: Roy
authors.forename: Brian C
authors.initials: BC
authors.lastname: Jung
authors.forename: Jason
authors.initials: J
authors.lastname: Diaz
authors.forename: Richard F
authors.initials: RF
authors.lastname: Macko
authors.forename: Larry W
authors.initials: LW
authors.lastname: Forrester
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000842:Ankle / Q000503:physiopathology*; D005081:Exercise Therapy / Q000379:methods*; D005260:Female; D005500:Follow-Up Studies; D020233:Gait Disorders, Neurologic / Q000209:etiology / Q000534:rehabilitation*; D006801:Humans; D008297:Male; D008875:Middle Aged; D009043:Motor Activity / Q000502:physiology*; D020127:Recovery of Function; D012371:Robotics / Q000379:methods*; D000071939:Stroke Rehabilitation; D016896:Treatment Outcome; D055815:Young Adult
keywords: EEG; EEG coherence; EEG spectral 
  power; ankle robotics; anklebot; chronic hemiparetic stroke; cognitive motor learning; gait; plasticity; reward