…Contains physiological recordings like eye-tracking (gaze coordinates and pupil size), and…
A multimodal dataset of human balance during beam walking and standing on a treadmill-mounted balance beam. It includes synchronized 128-channel EEG, lower leg and neck EMG, EOG, and motion capture. Participants were exposed to visual field rotations in virtual reality or physical side-to-side waist pulls, which allows electrocortical and muscular responses to sensorimotor perturbations to be compared.
…Contains physiological recordings like eye-tracking (gaze coordinates and pupil size), and…
…A Multi-Modal Dataset of EEG Signals and Virtual Glove Hand Tracking…
EEG recordings from four participants performing motor imagery of the left hand, right hand, and feet, originally reported by Zhou et al. (2016) in a study on automated trial selection for motor imagery brain-computer interfaces. Each participant completed three sessions of two runs, giving 450 trials per subject. Data were recorded from 14 channels at 250 Hz and reformatted into BIDS from a MOABB-generated Zenodo version.
The YOTO (You Only Think Once) dataset is a human EEG resource for studying multisensory perception and mental imagery. Twenty participants completed tasks with unimodal and multimodal (visual, auditory, and combined) cues while EEG was recorded at 1000 Hz, and they gave self-reported vividness ratings of their imagery. Technical validation with event-related potentials and power spectral density analyses confirmed data reliability and distinct neural responses across stimuli, supporting research on neural decoding, perception, and cognitive modeling.
[. The name suggests a lexical decision task with ocular measurements, but the README gives no details about participants, stimuli, or recording modality.
NOD-EEG is an electroencephalography dataset of human responses to naturalistic ImageNet object images. It extends the Natural Object Dataset-fMRI (NOD-fMRI) by recording EEG, and MEG in a companion dataset, from the same subjects viewing the same stimuli. Together the three modalities support study of object recognition with both high spatial and high temporal resolution. The dataset includes raw BIDS data, preprocessed continuous data, epoched data, and detailed trial-level metadata.