<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Norman, SL</style></author><author><style face="normal" font="default" size="100%">McFarland, DJ</style></author><author><style face="normal" font="default" size="100%">Miner, A</style></author><author><style face="normal" font="default" size="100%">Cramer, SC</style></author><author><style face="normal" font="default" size="100%">Wolbrecht, ET</style></author><author><style face="normal" font="default" size="100%">Jonathan Wolpaw</style></author><author><style face="normal" font="default" size="100%">Reinkensmeyer, DJ</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Controlling pre-movement sensorimotor rhythm can improve finger extension after stroke</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Neural Engineering</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">BCI</style></keyword><keyword><style  face="normal" font="default" size="100%">Motor control</style></keyword><keyword><style  face="normal" font="default" size="100%">Rehabilitation</style></keyword><keyword><style  face="normal" font="default" size="100%">robot</style></keyword><keyword><style  face="normal" font="default" size="100%">sensorimotor rhythm</style></keyword><keyword><style  face="normal" font="default" size="100%">Stroke</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2018</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://stacks.iop.org/1741-2552/15/i=5/a=056026</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">15</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Objective. Brain–computer interface (BCI) technology is attracting increasing interest as a tool for enhancing recovery of motor function after stroke, yet the optimal way to apply this technology is unknown. Here, we studied the immediate and therapeutic effects of BCI-based training to control pre-movement sensorimotor rhythm (SMR) amplitude on robot-assisted finger extension in people with stroke. Approach. Eight people with moderate to severe hand impairment due to chronic stroke completed a four-week three-phase protocol during which they practiced finger extension with assistance from the FINGER robotic exoskeleton. In Phase 1, we identified spatiospectral SMR features for each person that correlated with the intent to extend the index and/or middle finger(s). In Phase 2, the participants learned to increase or decrease SMR features given visual feedback, without movement. In Phase 3, the participants were cued to increase or decrease their SMR features, and when successful, were then cued to immediately attempt to extend the finger(s) with robot assistance. Main results. Of the four participants that achieved SMR control in Phase 2, three initiated finger extensions with a reduced reaction time after decreasing (versus increasing) pre-movement SMR amplitude during Phase 3. Two also extended at least one of their fingers more forcefully after decreasing pre-movement SMR amplitude. Hand function, measured by the box and block test (BBT), improved by 7.3  ±  7.5 blocks versus 3.5  ±  3.1 blocks in those with and without SMR control, respectively. Higher BBT scores at baseline correlated with a larger change in BBT score. Significance. These results suggest that learning to control person-specific pre-movement SMR features associated with finger extension can improve finger extension ability after stroke for some individuals. These results merit further investigation in a rehabilitation context.</style></abstract><issue><style face="normal" font="default" size="100%">5</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Thompson, AK</style></author><author><style face="normal" font="default" size="100%">Carruth, H</style></author><author><style face="normal" font="default" size="100%">Haywood, R</style></author><author><style face="normal" font="default" size="100%">Hill, NJ</style></author><author><style face="normal" font="default" size="100%">Sarnacki, WA</style></author><author><style face="normal" font="default" size="100%">McCane, LM</style></author><author><style face="normal" font="default" size="100%">Jonathan Wolpaw</style></author><author><style face="normal" font="default" size="100%">McFarland, DJ</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Effects of Sensorimotor Rhythm Modulation on the Human Flexor Carpi Radialis H-Reflex</style></title><secondary-title><style face="normal" font="default" size="100%">Frontiers in Neuroscience</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">brain-computer interface (BC)</style></keyword><keyword><style  face="normal" font="default" size="100%">EEG mu-rhythm</style></keyword><keyword><style  face="normal" font="default" size="100%">H-Reflex</style></keyword><keyword><style  face="normal" font="default" size="100%">Spinal Cord Injuries</style></keyword><keyword><style  face="normal" font="default" size="100%">task-dependent adaptation</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">07/2018</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.frontiersin.org/article/10.3389/fnins.2018.00505</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">12</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">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 (8–13 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 &lt; 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% ± 6 (mean ± SE)] during SMR-up trials than between trials, and significantly smaller (92% ± 1) during SMR-down trials than between trials (p &lt; 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.

</style></abstract><section><style face="normal" font="default" size="100%">505</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Jonathan Wolpaw</style></author><author><style face="normal" font="default" size="100%">Bedlack, RS</style></author><author><style face="normal" font="default" size="100%">Reda, DJ</style></author><author><style face="normal" font="default" size="100%">Ringer, RJ</style></author><author><style face="normal" font="default" size="100%">Banks, PG</style></author><author><style face="normal" font="default" size="100%">Vaughan, TM</style></author><author><style face="normal" font="default" size="100%">Heckman, SM</style></author><author><style face="normal" font="default" size="100%">McCrane, LM</style></author><author><style face="normal" font="default" size="100%">Carmack, CS</style></author><author><style face="normal" font="default" size="100%">Winden, S</style></author><author><style face="normal" font="default" size="100%">McFarland, DJ</style></author><author><style face="normal" font="default" size="100%">Sellers, EW</style></author><author><style face="normal" font="default" size="100%">Shi, H</style></author><author><style face="normal" font="default" size="100%">Paine, T</style></author><author><style face="normal" font="default" size="100%">Higgins, DS</style></author><author><style face="normal" font="default" size="100%">Lo, AC</style></author><author><style face="normal" font="default" size="100%">Patwa, HS</style></author><author><style face="normal" font="default" size="100%">Hill, KJ</style></author><author><style face="normal" font="default" size="100%">Huang, GS</style></author><author><style face="normal" font="default" size="100%">Ruff, RL</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Independent home use of a brain-computer interface by people with amyotrophic lateral sclerosis</style></title><secondary-title><style face="normal" font="default" size="100%">Neurology</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">All clinical neurophysiology</style></keyword><keyword><style  face="normal" font="default" size="100%">All Neuromuscular Disease</style></keyword><keyword><style  face="normal" font="default" size="100%">Evoked Potentials</style></keyword><keyword><style  face="normal" font="default" size="100%">visual</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">06/2018</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://n.neurology.org/content/neurology/early/2018/06/27/WNL.0000000000005812.full.pdf</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Objective: To assess the reliability and usefulness of an EEG-based brain-computer interface (BCI) for patients with advanced amyotrophic lateral sclerosis (ALS) who used it independently at home for up to 18 months.

Methods: Of 42 patients consented, 39 (93%) met the study criteria, and 37 (88%) were assessed for use of the Wadsworth BCI. Nine (21%) could not use the BCI. Of the other 28, 27 (men, age 28–79 years) (64%) had the BCI placed in their homes, and they and their caregivers were trained to use it. Use data were collected by Internet. Periodic visits evaluated BCI benefit and burden and quality of life.

Results: Over subsequent months, 12 (29% of the original 42) left the study because of death or rapid disease progression and 6 (14%) left because of decreased interest. Fourteen (33%) completed training and used the BCI independently, mainly for communication. Technical problems were rare. Patient and caregiver ratings indicated that BCI benefit exceeded burden. Quality of life remained stable. Of those not lost to the disease, half completed the study; all but 1 patient kept the BCI for further use.

Conclusion: The Wadsworth BCI home system can function reliably and usefully when operated by patients in their homes. BCIs that support communication are at present most suitable for people who are severely disabled but are otherwise in stable health. Improvements in BCI convenience and performance, including some now underway, should increase the number of people who find them useful and the extent to which they are used.</style></abstract></record></records></xml>