Showing 10 of 660 datasets · page 9 of 66
This dataset comprises high-density electroencephalography (EEG) recordings acquired during a visual stimulation task. Raw data are organized according to the EEG-BIDS specification and stored in BrainVision format. The dataset represents a single session of data collection and serves as a resource for investigating neural responses to visual stimuli.
A resting-state EEG dataset acquired from 128 channels at 1000 Hz sampling rate using an Electrical Geodesics amplifier system, complemented by structural MRI data from a GE MR750 scanner. The dataset includes preprocessed EEG signals with artifact removal and channel interpolation, as well as high-resolution anatomical imaging. This multimodal neuroimaging resource enables investigation of whole-brain electrophysiological functional connectivity dynamics during rest.
This dataset comprises intracranial EEG recordings from 23 patients with drug-resistant epilepsy undergoing stereo-EEG presurgical evaluation. The dataset includes 41 high-frequency stimulation events that evoked negative motor responses, with 24-second iEEG recordings per stimulation event (9-10 seconds pre-stimulation, up to 5 seconds stimulation, and 9-10 seconds post-stimulation). Stimulation parameters, contact pairs, current intensities, and evoked effects are documented in event files, enabling analysis of cortical responses to electrical stimulation.
This dataset comprises electroencephalography (EEG) recordings from young adult participants during resting state and auditory oddball task conditions. Data were collected under two experimental conditions: a control condition and a shock threat condition involving threat of unpredictable shock. The dataset includes both passive and active variants of the auditory oddball task, as well as resting state recordings with eyes open and closed, designed to investigate locus coeruleus-noradrenaline system function and its relationship to attention and arousal.
3M-CPSEED is an EEG dataset comprising recordings from 20 native Chinese speakers performing overt, silently articulated, and imagined speech tasks using Chinese Pinyin phonemes. The dataset captures neural activity across 6 initials (m, f, j, l, k, ch) and 4 finals (a, i, u, ü), with 1600 trials per participant. This resource supports investigation of neural mechanisms underlying speech production.
The LIGHT Hypnotherapy dataset comprises EEG and ECG recordings from guided imagery hypnotherapy sessions designed to enhance well-being through eudaemonic visualization techniques. This derivative dataset is derived from OpenNeuro ds006437 and includes physiological recordings from in-lab sessions with annotated hypnotherapist phase transitions. Participants underwent baseline resting EEG assessment followed by multiple hypnotherapy sessions incorporating structured visualization protocols (relaxation induction, imagined environments, guided descent, and emergence phases), providing a resource for investigating neural correlates of guided imagery and therapeutic hypnotherapy.
This dataset comprises EEG recordings from three experiments investigating the effects of selective attention on auditory brainstem and cortical responses to natural speech. Participants listened to audiobook narrations under different stimulus configurations (diotic, dichotic, and passive listening conditions) while EEG was recorded from both cortical (32-channel active montage) and subcortical (passive bipolar montage) electrode arrays. The study examines whether selective attention modulates the auditory brainstem response to natural speech stimuli.
This dataset contains electrophysiological recordings from 33 participants performing visual and auditory surprise detection tasks. The study investigates electrophysiological markers associated with surprise-induced failures of awareness across sensory modalities. EEG data were collected during counterbalanced presentation of visual and auditory oddball-like tasks, with detailed event annotations and preprocessing information provided for reproducibility.
This BIDS dataset demonstrates the application of the Hierarchical Event Descriptor (HED) schema library for Standardized Computer-based Organized Reporting of EEG (SCORE) to annotate intracranial EEG recordings. The dataset contains iEEG data from a single subject acquired during clinical photic stimulation at Mayo Clinic Rochester, with machine-readable event annotations validated against both BIDS and HED standards.
PhysioMotion_Artifact is an electrophysiological dataset organized in BIDS format containing EEG recordings with associated physiological motion artifacts. The dataset serves as a resource for studying and developing artifact detection and correction methods in EEG analysis, with potential applications in motor imagery and brain-computer interface research.