100 results for "Brain-Computer Interfaces" · page 9 of 10 · ranked by relevance
…user-centered design ## Abstract Brain–computer interfaces (BCIs) based on event related…
MIPDB is a multimodal neuroimaging resource comprising high-density EEG (128-channel, 500 Hz) and eye-tracking data collected from 111 participants spanning childhood to adulthood. Participants completed a standardized battery of cognitive and perceptual tasks including resting state, surround suppression, naturalistic viewing, contrast-change detection, sequence learning, and symbol search. This dataset enables investigation of information-processing maturation across human development.
…in brain-computer interfaces (BCIs) is to tune a brain signal decoder…
…School of Electrical Engineering and Computer Science, GIST - **Country**: KR - **Repository**: Figshare…
This dataset comprises simultaneous EEG-fMRI recordings from 24 healthy adults performing a sustained attention task (GradCPT) and a resting-state task with intermittent multi-dimensional experience sampling, collected across two sessions per participant. It includes behavioral responses, experience sampling ratings across 13 dimensions of thought, and mental health survey data, enabling study of the neural correlates of attentional fluctuations, mind-wandering, and the reliability of EEG-fMRI relationships across sessions.
…High-density scalp electroencephalogram dataset during sensorimotor rhythm-based brain-computer interfacing…
…High-density scalp electroencephalogram dataset during sensorimotor rhythm-based brain-computer interfacing…
This dataset comprises multimodal physiological recordings from 86 participants during resting state and a digit span working memory task. It includes 64-channel EEG, electrocardiography, photoplethysmography, pupillometry, and behavioral performance data. The dataset enables investigation of neural and peripheral physiological correlates of cognitive load, working memory capacity, and cognitive overload detection across fine temporal scales.
An EEG study investigating the effects of episodic future thinking on temporal discounting behavior. Participants generated descriptions of future events and subsequently used mental imagery of these events as cues during intertemporal choice tasks, with concurrent measurement of imagery vividness. This dataset provides neurophysiological recordings during decision-making processes influenced by prospective cognition.
…High-density scalp electroencephalogram dataset during sensorimotor rhythm-based brain-computer interfacing…