An fNIRS dataset for driving risk cognition of passengers in highly automated driving scenarios
[ recordings collected during the presentation of stylized facial stimuli to investigate emotion detection and event-related potentials (ERPs). The study demonstrates that artificially enhanced faces with exaggerated visual features elicit enhanced N170 components compared to standard facial images, suggesting optimized stimulus design can improve neural correlates of emotion recognition. These findings have implications for affective brain-computer interface (BCI) development and emotion detection accuracy from EEG signals. Participant information has been anonymized.
[ recordings from a face perception task conducted across three undergraduate institutions. Data were collected from participants in 2017-2018 using a standardized task design documented in the ERP CORE resource. This dataset provides a multisite contribution to open-access human electrophysiological research on face processing and the N170 component.
[ and flash types (standard flash or cartoon face overlay). EEG data were acquired from eight scalp electrodes at 256 Hz sampling rate, with detailed event markers encoding experimental phases and stimulus presentations.
[ recordings from a visual oddball task collected as part of the PURSUE project across three primarily undergraduate institutions. Participants performed a P300 oddball paradigm while EEG was recorded in 2017-2018. This dataset is one of the standardized ERP CORE initiative datasets, an open resource for standardized human event-related potential research.