BNCI 2014-009 P300 dataset
…Eight stimulation sequences per trial with 16 target intensifications. - **Feedback type**: none…
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100 results for "brain stimulation" · page 10 of 10 · ranked by relevance
…Eight stimulation sequences per trial with 16 target intensifications. - **Feedback type**: none…
…MEG-BIDS, the brain imaging data structure extended to magnetoencephalography. Scientific Data…
A multi-paradigm EEG dataset comprising scalp electroencephalography recordings from 28 participants performing and imagining upper-limb rehabilitation exercises. This dataset is designed to support research on motor imagery and rehabilitation brain-computer interfaces (BCI) for upper-limb motor function recovery and assessment.
…all subjects) and electrical muscle stimulation (EMS) feedback (10 subjects) . In 25…
…It is consisted of eyes-open EEG recordings in multiple photic stimulation…
The Brain, Body, and Behaviour Dataset - Experiment 3 is a multimodal neurophysiological dataset comprising 29 subjects across 2 sessions designed to investigate the effects of attentional state on learning from educational videos. Participants watched six educational videos under two conditions: attentive (with post-video testing) and distracted (with concurrent cognitive load), while simultaneous recordings of brain activity, cardiovascular function, eye movements, and head motion were collected. The dataset includes concurrent EEG, ECG, EOG, gaze tracking, pupil size, and head position data, along with behavioral measures including memory questionnaires and ADHD symptom assessments.
[ Software: BBCI Toolbox (MATLAB) Reference: nose Sensor type…
The Brain, Body, and Behaviour Dataset (Experiment 4) is a multimodal neurophysiological dataset comprising simultaneous recordings of EEG, eye-tracking, cardiac, respiratory, and electrooculographic signals from 43 subjects across two sessions. Participants watched three educational videos (Stim-04, Stim-05, Stim-06) under two attention conditions. In Session 1 (attentive condition), participants viewed the videos and answered comprehension questions afterward. In Session 2 (distracted condition), participants viewed the same three videos in the same order while performing a concurrent backward counting task, with no comprehension testing. This derivative dataset supports investigation of neural and behavioral correlates of attention, learning, and cognitive load during naturalistic video viewing.