100 results for "motor imagery" · page 8 of 10 · ranked by relevance
…4-class motor imagery dataset BNCI2014_004 : 2-class motor imagery dataset…
This dataset comprises multimodal neurophysiological and biomechanical recordings from 32 young adults performing walking tasks over uneven terrain at varying speeds. Data include high-density dual-layer electroencephalography (EEG), neck electromyography (EMG), inertial measurement unit (IMU) acceleration, ground reaction forces, and structural MRI-derived head models. Each participant completed two trials per condition lasting three minutes, plus a seated rest baseline, providing a comprehensive resource for investigating neural and muscular control mechanisms during dynamic locomotion.
THINGS-EEG2 is a large-scale EEG dataset comprising recordings from 10 subjects viewing 16,540 distinct training images and 200 test images presented via rapid serial visual presentation at 5 Hz. The dataset includes 63-channel EEG data sampled at 1000 Hz across 4 sessions per subject, with approximately 32,540 training trials and 16,000 test trials, designed to support computational modeling of human visual object recognition. Stimuli are drawn from the THINGS database, and the dataset includes resting-state recordings and behavioral annotations for each trial.
This dataset comprises preprocessed EEG recordings from 16 native French-speaking participants performing a forced picture naming task. Participants viewed images from the Snodgrass & Vanderwart corpus and were required to name them while EEG activity was recorded across baseline, visual stimulation, and naming phases. The dataset contains 270 trials per subject and was used to characterize spatiotemporal dynamics in EEG data using optical flow pattern analysis. Note: 16 participants represent the final cohort after 4 exclusions from an initial 20 subjects due to hardware failure.
…motor_imagery - **Imagery tasks**: hand_open_close, wrist_flex_ext, wrist_abd…
…motor_imagery Number of repetitions: 20 Data Structure -------------- Trials: {'per_session': 20…
Imported from OpenNeuro ds003801
THINGS-MEG is a large-scale magnetoencephalographic dataset comprising neural recordings from participants viewing thousands of photographic images representing 1,854 object concepts from the THINGS database. This dataset is part of the multimodal THINGS-data collection, which integrates MEG recordings with behavioral judgments and complementary neuroimaging modalities to enable comprehensive investigation of visual and semantic object processing. The dataset includes structural MRI for source localization and eye-tracking data, providing rich temporal and spatial dynamics of object representations across the brain.
…motor_imagery - **Imagery tasks**: left_hand_finger_tapping, right_hand_finger_tapping…
This dataset comprises synchronized multimodal neurophysiological and biomechanical recordings from 128-channel EEG, electromyography (EMG), electrooculography (EOG), and motion capture during a perturbed beam-walking task. Participants performed four 10-minute sessions of standing or walking on a narrow balance beam while exposed to sensorimotor perturbations (visual field rotations or waist pulls). The dataset includes preprocessed EEG data with identified good channels and independent component analysis results, enabling investigation of cortical mechanisms underlying balance control and responses to perturbations.