%0 Journal Article %J Brain Comput Interfaces (Abingdon) %D 2022 %T Workshops of the Eighth International Brain-Computer Interface Meeting: BCIs: The Next Frontier. %A Huggins, Jane E %A Krusienski, Dean %A Vansteensel, Mariska J %A Valeriani, Davide %A Thelen, Antonia %A Stavisky, Sergey %A Norton, James J S %A Nijholt, Anton %A Müller-Putz, Gernot %A Kosmyna, Nataliya %A Korczowski, Louis %A Kapeller, Christoph %A Herff, Christian %A Halder, Sebastian %A Guger, Christoph %A Grosse-Wentrup, Moritz %A Gaunt, Robert %A Dusang, Aliceson Nicole %A Clisson, Pierre %A Chavarriaga, Ricardo %A Anderson, Charles W %A Allison, Brendan Z %A Aksenova, Tetiana %A Aarnoutse, Erik %X

The Eighth International Brain-Computer Interface (BCI) Meeting was held June 7-9th, 2021 in a virtual format. The conference continued the BCI Meeting series' interactive nature with 21 workshops covering topics in BCI (also called brain-machine interface) research. As in the past, workshops covered the breadth of topics in BCI. Some workshops provided detailed examinations of specific methods, hardware, or processes. Others focused on specific BCI applications or user groups. Several workshops continued consensus building efforts designed to create BCI standards and increase the ease of comparisons between studies and the potential for meta-analysis and large multi-site clinical trials. Ethical and translational considerations were both the primary topic for some workshops or an important secondary consideration for others. The range of BCI applications continues to expand, with more workshops focusing on approaches that can extend beyond the needs of those with physical impairments. This paper summarizes each workshop, provides background information and references for further study, presents an overview of the discussion topics, and describes the conclusion, challenges, or initiatives that resulted from the interactions and discussion at the workshop.

%B Brain Comput Interfaces (Abingdon) %V 9 %P 69-101 %8 2022 %G eng %N 2 %R 10.1080/2326263X.2021.2009654 %0 Journal Article %J Journal of Neural Engineering %D 2019 %T An exploration of BCI performance variations in people with amyotrophic lateral sclerosis using longitudinal EEG data %A Shahriari, Yalda %A Vaughan, Theresa %A McCane, Lynn %A Allison, Brendan %A Wolpaw, Jonathan %A Krusienski, Dean %K amyotrophic lateral sclerosis (ALS) %K Brain-computer interface (BCI) %K Longitudinal Electroencephalogram (EEG) %K P300 speller %X 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 (<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. %B Journal of Neural Engineering %8 05/2019 %G eng %U https://iopscience.iop.org/article/10.1088/1741-2552/ab22ea %R 10.1088/1741-2552/ab22ea