@article {4110,
	title = {Effects of Sensorimotor Rhythm Modulation on the Human Flexor Carpi Radialis H-Reflex},
	journal = {Frontiers in Neuroscience},
	volume = {12},
	year = {2018},
	month = {07/2018},
	chapter = {505},
	abstract = {People can learn over training sessions to increase or decrease sensorimotor rhythms (SMRs) in the electroencephalogram (EEG). Activity-dependent brain plasticity is thought to guide spinal plasticity during motor skill learning; thus, SMR training may affect spinal reflexes and thereby influence motor control. To test this hypothesis, we investigated the effects of learned mu (8{\textendash}13 Hz) SMR modulation on the flexor carpi radialis (FCR) H-reflex in 6 subjects with no known neurological conditions and 2 subjects with chronic incomplete spinal cord injury (SCI). All subjects had learned and practiced over more than 10 < 30-min training sessions to increase (SMR-up trials) and decrease (SMR-down trials) mu-rhythm amplitude over the hand/arm area of left sensorimotor cortex with >=80\% accuracy. Right FCR H-reflexes were elicited at random times during SMR-up and SMR-down trials, and in between trials. SMR modulation affected H-reflex size. In all the neurologically normal subjects, the H-reflex was significantly larger [116\% {\textpm} 6 (mean {\textpm} SE)] during SMR-up trials than between trials, and significantly smaller (92\% {\textpm} 1) during SMR-down trials than between trials (p < 0.05 for both, paired t-test). One subject with SCI showed similar H-reflex size dependence (high for SMR-up trials, low for SMR-down trials): the other subject with SCI showed no dependence. These results support the hypothesis that SMR modulation has predictable effects on spinal reflex excitability in people who are neurologically normal; they also suggest that it might be used to enhance therapies that seek to improve functional recovery in some individuals with SCI or other CNS disorders.

},
	keywords = {brain-computer interface (BC), EEG mu-rhythm, H-Reflex, Spinal Cord Injuries, task-dependent adaptation},
	issn = {1662-453X},
	doi = {10.3389/fnins.2018.00505},
	url = {https://www.frontiersin.org/article/10.3389/fnins.2018.00505},
	author = {Thompson, AK and Carruth, H and Haywood, R and Hill, NJ and Sarnacki, WA and McCane, LM and Jonathan Wolpaw and McFarland, DJ}
}
