Alex Motor Imagery dataset
…visual cue - **Stimulus modalities**: visual, auditory - **Primary modality**: visual - **Synchronicity**: synchronous - **Mode…
- Size
- 99.6 MB
- Updated
- May 16, 2026
100 results for "cue-response mapping" · page 9 of 10 · ranked by relevance
…visual cue - **Stimulus modalities**: visual, auditory - **Primary modality**: visual - **Synchronicity**: synchronous - **Mode…
Imported from OpenNeuro ds003801
…Participants responded using a button press, with a maximum response time of…
…EEG Responses to Natural Images ## Overview Alljoined1 is an EEG dataset of…
…The following mapping is used: - 0: Sleep stage W (Wake) - 1: Sleep…
The Brain, Body, and Behaviour Dataset (Experiment 2) is a multimodal neurophysiological dataset comprising 31 subjects across 2 sessions designed to investigate incidental learning and attentional modulation. Participants watched five educational videos under attentive and distracted conditions while simultaneous recordings of EEG, ECG, EOG, eye-tracking, and pupil dynamics were acquired. This derivative dataset includes preprocessed physiological signals and behavioral responses to memory questionnaires, providing a comprehensive resource for studying the neural and physiological correlates of attention, learning, and cognitive load.
The MNE-Sample-Data dataset comprises simultaneous MEG and EEG recordings acquired from a single subject using a Neuromag Vectorview system at the Martinos Center for Biomedical Imaging. The experiment involved visual stimulation (checkerboard patterns presented to left and right visual fields) and auditory stimulation (tones to left and right ears), with occasional face stimuli requiring motor responses. Structural MRI data from a 1.5 T Siemens scanner and Freesurfer-derived anatomical derivatives are included, providing a comprehensive reference dataset for MEG/EEG analysis and method development.
This dataset contains electroencephalogram (EEG), galvanic skin response (GSR), and electrocardiogram (ECG) recordings from 19 healthy adult participants during a calibration session of an affective brain-computer music interface system. Participants listened to 40-second synthetic music clips designed to induce specific affective states defined by valence and arousal dimensions across 5 runs of 18 trials each. The synthetic music was generated in real-time based on target emotional states and could be modified online to induce target emotional states. The dataset includes self-reported affective state ratings and auxiliary variables, serving as calibration data for the brain-computer music interface system. This dataset is part of a three-dataset collection that includes offline training and online real-time control sessions.