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• W2340678003 abstract "Abstract 13 Objective. The ability of an automobile to infer the driver’s upcoming actions directly 14 from neural signals could enrich the interaction of the car with its driver. Intelligent 15 vehicles tted with an on-board brain-computer interface (BCI) able to decode the 16 driver’s intentions can use this information to improve the driving experience. In 17 this study we investigate the neural signatures of anticipation of speci c actions, 18 namely braking and accelerating. Approach. We investigated anticipatory slow cortical 19 potentials (SCPs) in electroencephalogram (EEG) recorded from 18 healthy participants 20 in a driving simulator using a variant of the contingent negative variation (CNV) 21 paradigm with Go and No-go conditions: count-down numbers followed by ‘Start’/‘Stop’ 22 cue. We report decoding performance before the action onset using a quadratic 23 discriminant analysis (QDA) classi er based on temporal features. Main Results. (i) 24 Despite the visual and driving related cognitive distractions, we show the presence of" @default.
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• W2340678003 date "2015-01-01" @default.
• W2340678003 modified "2023-10-01" @default.
• W2340678003 title "Action Prediction Based on Anticipatory Brain" @default.
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