electroencephalography (M/EEG). Bad trials are commonly identified using peak-to-peak
rejection thresholds that are set manually. This work proposes a solution to determine them
automatically using cross-validation. We show that automatically selected rejection
thresholds perform at par with manual thresholds, which can save hours of visual data
inspection. We then use this automated approach to learn a sensor-specific rejection …