02632nas a2200217   4500008004100000245012200041210006900163260001200232520184800244653004002092653003502132653004402167653001702211100002102228700002102249700001702270700002102287700002102308700002102329856006402350       2019                        eng d00aAn exploration of BCI performance variations in people with amyotrophic lateral sclerosis using longitudinal EEG data0 aexploration of BCI performance variations in people with amyotro  c05/20193 aObjective. 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.10aamyotrophic lateral sclerosis (ALS)10aBrain-computer interface (BCI)10aLongitudinal Electroencephalogram (EEG)10aP300 speller1 aShahriari, Yalda1 aVaughan, Theresa1 aMcCane, Lynn1 aAllison, Brendan1 aWolpaw, Jonathan1 aKrusienski, Dean  uhttps://iopscience.iop.org/article/10.1088/1741-2552/ab22ea01649nas a2200241   4500008004100000022001400041245004600055210004500101260001200146300001200158490000800170520095000178653002901128653002901157653001701186653004201203100002301245700002001268700002601288700002401314700002101338856004801359       2008                        eng d  a0165-027000aToward enhanced P300 speller performance.0 aToward enhanced P300 speller performance  c01/2008  a15–210 v1673 aThis study examines the effects of expanding the classical P300 feature space on the classification performance of data collected from a P300 speller paradigm [Farwell LA, Donchin E. Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials. Electroenceph Clin Neurophysiol 1988;70:510-23]. Using stepwise linear discriminant analysis (SWLDA) to construct a classifier, the effects of spatial channel selection, channel referencing, data decimation, and maximum number of model features are compared with the intent of establishing a baseline not only for the SWLDA classifier, but for related P300 speller classification methods in general. By supplementing the classical P300 recording locations with posterior locations, online classification performance of P300 speller responses can be significantly improved using SWLDA and the favorable parameters derived from the offline comparative analysis.10abrain-computer interface10aevent related potentials10aP300 speller10astepwise linear discriminant analysis1 aKrusienski, D., J.1 aSellers, E., W.1 aMcFarland, Dennis, J.1 aVaughan, Theresa, M1 aWolpaw, Jonathan  uhttp://www.ncbi.nlm.nih.gov/pubmed/17822777