on004368
Meta-rdk: Preprocessed EEG data
EEG
Imported from OpenNeuro ds004368
- Participants
- 39
- Channels
- 63 (10-10)
- Size
- 969 MB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
Discover datasets
91 results for "stereo-encephalography" · page 5 of 10 · ranked by relevance
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- on004362
EEG Motor Movement/Imagery Dataset
EEGImported from OpenNeuro ds004362
- Participants
- 109
- Channels
- 64 (10-10)
- Citations
- 99
- HED
- v8.1.0
- Size
- 11.1 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- nm000250
Dreyer et al. 2023 — A large EEG database with users' profile information for motor imagery brain-computer interface research
EEGA comprehensive EEG database containing electroencephalographic signals from 87 healthy participants performing motor imagery brain-computer interface tasks. The dataset comprises over 20,800 trials (~70 hours of recording) organized into three datasets (A, B, C) using a standardized Graz protocol for right and left hand motor imagery. In addition to raw EEG signals, the database includes detailed participant demographics, personality profiles, cognitive traits, and BCI performance metrics, enabling research on user-performance relationships, cross-user machine learning algorithms, and profile-informed signal classification.
- Participants
- 87
- Channels
- 27 (10-10)
- Citations
- 38
- HED
- v8.4.0
- Size
- 15.8 GB
- Version
- v1.0.4
- Updated
- Aug 18, 2026
- nm000199
Learning from label proportions for a visual matrix speller (ERP)
EEGThis dataset comprises event-related potential (ERP) recordings from 13 healthy subjects performing a visual matrix speller task using a calibrationless brain-computer interface approach. The study introduces learning from label proportions (LLP), an unsupervised classification method that exploits known target/non-target stimulus ratios to enable online BCI operation without prior calibration. Subjects performed copy-spelling tasks using a 6×7 character grid across three sessions, achieving 84.5% character accuracy without labeled training data.
- Participants
- 13
- Channels
- 31 (10-10)
- Citations
- 46
- HED
- v8.4.0
- Size
- 5.15 GB
- Version
- v1.0.2
- Updated
- Aug 18, 2026
- on005810
NOD-MEG
ANAT MEGNOD-MEG provides magnetoencephalography (MEG) recordings from human participants viewing large-scale naturalistic ImageNet stimuli, extending the previously collected Natural Object Dataset (NOD-fMRI) with temporally resolved neural data. Combined with corresponding fMRI and EEG datasets from the same subjects, NOD-MEG enables multimodal investigation of object recognition across both spatial and temporal domains. The dataset is intended as a resource for studying neural mechanisms of visual object recognition under naturalistic viewing conditions.
- Participants
- 31
- Citations
- 1
- Size
- 215 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026
- on007012
FOODEEG: An open dataset of human electroencephalographic and behavioural responses to food images
BEH EEGFOODEEG is an open dataset of electroencephalographic (EEG) and behavioural responses to food images from 117 participants across two testing sessions. Session 1 involved a food categorisation task with continuous EEG recording, while Session 2 comprised a food go/no-go task and a food paired choice task, along with questionnaires on dietary style and eating motivations. The dataset also includes normative ratings on 22 food attributes collected from an independent online sample (N = 624), providing a rich resource for studying neural and behavioural correlates of food-related decision-making.
- Participants
- 117
- Size
- 91.1 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026
- on006171
EEG data during three near-threshold visual detection tasks: a no-cue task, a noninformative cue task (50% validity), and an informative cue task (100% validity)
EEGThis dataset contains EEG recordings collected during three near-threshold visual detection tasks: a no-cue task, a noninformative cue task (50% validity), and an informative cue task (100% validity). The study investigates how attentional cueing and prestimulus neural activity, particularly alpha-band oscillations, influence the perception of near-threshold visual stimuli. Data were collected to examine the interplay between attention and perceptual awareness in a visual detection paradigm.
- Participants
- 36
- Channels
- 128 (10-05)
- Citations
- 8
- Size
- 67.8 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026
- on004624
Intracranial recordings using BCI2000 and the CorTec BrainInterchange
ANAT iEEGThis dataset comprises intracranial EEG recordings collected using the CorTec BrainInterchange implantable device and the BCI2000 software platform, developed as part of an ecosystem of technology and protocols for adaptive neuromodulation research in humans. The data support research into closed-loop neuromodulation approaches and adaptive brain-computer interface systems. Recordings were obtained under IACUC-approved protocols in collaboration with Mayo Clinic and academic partners.
- Participants
- 3
- Size
- 19.3 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026
- on002158
Disentangling the origins of confidence in speeded perceptual judgments through multimodal imaging
ANAT EEG FMAP FUNCThis multimodal neuroimaging dataset investigates the neural mechanisms of metacognition—the ability to assess decision confidence—by isolating postdecisional from decisional contributions. Healthy volunteers performed perceptual judgments and observed decisions while reporting confidence, with concurrent electroencephalography and functional magnetic resonance imaging recordings. The study reveals dissociable neural correlates of confidence in prefrontal regions and proposes a computational model explaining how decision commitment enhances metacognitive performance.
- Participants
- 20
- Size
- 429 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- on004460
EEG and motion capture data set for a full-body/joystick rotation task
EEG MOTIONThis dataset comprises simultaneous EEG and motion capture recordings from 20 healthy adults performing a spatial orientation task involving full-body heading changes. Participants completed a spot rotation task under two conditions: joystick-controlled visual rotation on a 2D display and physical full-body rotation in a virtual reality environment. The dataset includes 157-channel EEG data (129 scalp + 28 neck electrodes) sampled at 1000 Hz and multi-camera motion capture data at 90 Hz, enabling investigation of cortical dynamics and sensorimotor integration during naturalistic spatial navigation.
- Participants
- 20
- Channels
- 160 (other)
- Citations
- 39
- Size
- 61.4 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026