@article {4363,
	title = {Recommendations for Responsible Development and Application of Neurotechnologies.},
	journal = {Neuroethics},
	volume = {14},
	year = {2021},
	month = {2021},
	pages = {365-386},
	abstract = {<p>Advancements in novel neurotechnologies, such as brain computer interfaces (BCI) and neuromodulatory devices such as deep brain stimulators (DBS), will have profound implications for society and human rights. While these technologies are improving the diagnosis and treatment of mental and neurological diseases, they can also alter individual agency and estrange those using neurotechnologies from their sense of self, challenging basic notions of what it means to be human. As an international coalition of interdisciplinary scholars and practitioners, we examine these challenges and make recommendations to mitigate negative consequences that could arise from the unregulated development or application of novel neurotechnologies. We explore potential ethical challenges in four key areas: identity and agency, privacy, bias, and enhancement. To address them, we propose (1) democratic and inclusive summits to establish globally-coordinated ethical and societal guidelines for neurotechnology development and application, (2) new measures, including "Neurorights," for data privacy, security, and consent to empower neurotechnology users{\textquoteright} control over their data, (3) new methods of identifying and preventing bias, and (4) the adoption of public guidelines for safe and equitable distribution of neurotechnological devices.</p>},
	issn = {1874-5490},
	doi = {10.1007/s12152-021-09468-6},
	author = {Goering, Sara and Klein, Eran and Specker Sullivan, Laura and Wexler, Anna and Ag{\"u}era Y Arcas, Blaise and Bi, Guoqiang and Carmena, Jose M and Fins, Joseph J and Friesen, Phoebe and Gallant, Jack and Huggins, Jane E and Kellmeyer, Philipp and Marblestone, Adam and Mitchell, Christine and Parens, Erik and Pham, Michelle and Rubel, Alan and Sadato, Norihiro and Teicher, Mina and Wasserman, David and Whittaker, Meredith and Wolpaw, Jonathan and Yuste, Rafael}
}
@article {4235,
	title = {An exploration of BCI performance variations in people with amyotrophic lateral sclerosis using longitudinal EEG data},
	journal = {Journal of Neural Engineering},
	year = {2019},
	month = {05/2019},
	abstract = {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.},
	keywords = {amyotrophic lateral sclerosis (ALS), Brain-computer interface (BCI), Longitudinal Electroencephalogram (EEG), P300 speller},
	doi = {10.1088/1741-2552/ab22ea},
	url = {https://iopscience.iop.org/article/10.1088/1741-2552/ab22ea},
	author = {Shahriari, Yalda and Vaughan, Theresa and McCane, Lynn and Allison, Brendan and Wolpaw, Jonathan and Krusienski, Dean}
}
