<?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%">D.J. McFarland</style></author><author><style face="normal" font="default" size="100%">S.L. Norman</style></author><author><style face="normal" font="default" size="100%">W.A. Sarnacki</style></author><author><style face="normal" font="default" size="100%">E.T. Wolbrecht</style></author><author><style face="normal" font="default" size="100%">D.J. Reinkensmeyer</style></author><author><style face="normal" font="default" size="100%">J.R. Wolpaw</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">BCI-based sensorimotor rhythm training can affect individuated finger movements </style></title><secondary-title><style face="normal" font="default" size="100%">Brain Computer Interface Society</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">BCI</style></keyword><keyword><style  face="normal" font="default" size="100%">movement preparation</style></keyword><keyword><style  face="normal" font="default" size="100%">Rehabilitation</style></keyword><keyword><style  face="normal" font="default" size="100%">Robotics</style></keyword><keyword><style  face="normal" font="default" size="100%">sensorimotor beta rhythms</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">06/2020</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.tandfonline.com/doi/abs/10.1080/2326263X.2020.1763060?journalCode=tbci20</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">7</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Brain-computer interface (BCI) technology can restore communication and control to people who are severely paralyzed. BCI technology might also be able to enhance rehabilitation of motor function. We have previously shown that pre-movement sensorimotor rhythm (SMR) amplitude affects reaction time and performance on a joystick-based cursor movement task. The present study explores in adults without motor impairment the possibility that pre-movement SMR amplitude affects performance of individuated finger movements. In Phase 1, 8 individuals performed a finger flexion task that was monitored by an exoskeleton. During a 1-sec preparatory period, two colored targets on a video monitor cued flexion of the index finger, middle finger, both fingers, or neither finger; sudden color change then triggered the movement (or non-movement). SMR features (i.e. EEG amplitudes in specific frequency bands at specific scalp locations) in the pre-movement EEG that correlated with movement versus no movement were identified. In Phase 2, the participants learned to increase or decrease these SMR features to control a two-target BCI task. Finally, in Phase 3, they were asked to increase or decrease the SMR features to initiate the finger flexion task of Phase 1 and the impact on finger flexion performance was assessed. After BCI training, pre-movement SMR feature amplitude affected performance in a subset of individuals: lower amplitude was associated with shorter movement onset. In a subset of individuals, the beneficial effect on performance of lower SMR amplitude was greater when both fingers were flexed than when one was flexed and the other remained extended; thus, the impact of SMR amplitude modulation depended on the specificity of the subsequent motor task. These results indicate that BCI-based training of SMR activity in the pre-movement preparatory period can affect finger movements in a subset of individuals. They encourage studies that integrate such training into rehabilitation protocols and examine its capacity to enhance restoration of useful hand function.</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><section><style face="normal" font="default" size="100%">38</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">D.J. McFarland</style></author><author><style face="normal" font="default" size="100%">T.M. Vaughan</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Damien Coyle</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Chapter 13 - BCI in practice</style></title><secondary-title><style face="normal" font="default" size="100%">Brain-Computer Interfaces: Lab Experiments to Real-World Applications</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Progress in Brain Research</style></tertiary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Brain–computer interface</style></keyword><keyword><style  face="normal" font="default" size="100%">Home use</style></keyword><keyword><style  face="normal" font="default" size="100%">Neurotechnologies</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2016</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.sciencedirect.com/science/article/pii/S0079612316300917</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Elsevier</style></publisher><volume><style face="normal" font="default" size="100%">228</style></volume><pages><style face="normal" font="default" size="100%">389 - 404</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Brain–computer interfaces are systems that use signals recorded from the brain to enable communication and control applications for individuals who have impaired function. This technology has developed to the point that it is now being used by individuals who can actually benefit from it. However, there are several outstanding issues that prevent widespread use. These include the ease of obtaining high-quality recordings by home users, the speed, and accuracy of current devices and adapting applications to the needs of the user. In this chapter, we discuss some of these unsolved issues.</style></abstract></record></records></xml>