<?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%">Shahriari, Yalda</style></author><author><style face="normal" font="default" size="100%">Vaughan, Theresa</style></author><author><style face="normal" font="default" size="100%">McCane, Lynn</style></author><author><style face="normal" font="default" size="100%">Allison, Brendan</style></author><author><style face="normal" font="default" size="100%">Wolpaw, Jonathan</style></author><author><style face="normal" font="default" size="100%">Krusienski, Dean</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">An exploration of BCI performance variations in people with amyotrophic lateral sclerosis using longitudinal EEG data</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%">amyotrophic lateral sclerosis (ALS)</style></keyword><keyword><style  face="normal" font="default" size="100%">Brain-computer interface (BCI)</style></keyword><keyword><style  face="normal" font="default" size="100%">Longitudinal Electroencephalogram (EEG)</style></keyword><keyword><style  face="normal" font="default" size="100%">P300 speller</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">05/2019</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://iopscience.iop.org/article/10.1088/1741-2552/ab22ea</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. Brain-computer interface (BCI) technology enables people to use direct measures of brain activity for communication and control. The National Center for Adaptive Neurotechnologies (NCAN) and Helen Hayes Hospital are studying long-term independent home use of P300-based BCIs by people with amyotrophic lateral sclerosis (ALS). This BCI use takes place without technical oversight, and users can encounter substantial variation in their day-to-day BCI performance. The purpose of this study is to identify and evaluate features in the electroencephalogram (EEG) that correlate with successful BCI performance during home use with the goal of improving BCI for people with neuromuscular disorders. Approach. Nine people with ALS used a P300-based BCI at home over several months for communication and computer control. Sessions from a routine calibration task were categorized as successful (≥70%) or unsuccessful (&lt;70%) BCI performance. The correlation of temporal and spectral EEG features with BCI performance was then evaluated. Main Results. BCI performance was positively correlated with an increase in alpha-band (8-14 Hz) activity at locations PO8, P3, Pz, and P4; and beta-band (15-30 Hz) activity at occipital locations. In addition, performance was significantly positively correlated with a positive deflection in EEG amplitude around 220 ms at frontal mid-line locations (i.e., Fz and Cz). BCI performance was negatively correlated with delta-band (1-3 Hz) activity recorded from occipital locations. Significance. These results highlight the variability found in the EEG and describe EEG features that correlate with successful BCI performance during day-to-day use of a P300-based BCI by people with ALS. These results should inform studies focused on improved BCI reliability for people with neuromuscular disorders.</style></abstract></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%">Loeb, Gerald E.</style></author><author><style face="normal" font="default" size="100%">Brendan Z. Allison</style></author><author><style face="normal" font="default" size="100%">Emanuel Donchin</style></author><author><style face="normal" font="default" size="100%">do Nascimento, Omar Feix</style></author><author><style face="normal" font="default" size="100%">Heetderks, William J.</style></author><author><style face="normal" font="default" size="100%">Nijboer, Femke</style></author><author><style face="normal" font="default" size="100%">Shain, William G.</style></author><author><style face="normal" font="default" size="100%">Turner, James N.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">BCI Meeting 2005–workshop on signals and recording methods.</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Brain-computer interface (BCI)</style></keyword><keyword><style  face="normal" font="default" size="100%">electrophysiological signals</style></keyword><keyword><style  face="normal" font="default" size="100%">Rehabilitation</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">06/2006</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/16792279</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">14</style></volume><pages><style face="normal" font="default" size="100%">138–141</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This paper describes the highlights of presentations and discussions during the Third International BCI Meeting in a workshop that evaluated potential brain-computer interface (BCI) signals and currently available recording methods. It defined the main potential user populations and their needs, addressed the relative advantages and disadvantages of noninvasive and implanted (i.e., invasive) methodologies, considered ethical issues, and focused on the challenges involved in translating BCI systems from the laboratory to widespread clinical use. The workshop stressed the critical importance of developing useful applications that establish the practical value of BCI technology.</style></abstract></record></records></xml>