on005261
Gloups_MEG
BEH MEG
Imported from OpenNeuro ds005261
- Participants
- 17
- Size
- 225 GB
- Version
- v1.0.0
- Updated
- May 23, 2026
Discover datasets
Showing 10 of 60 datasets · page 1 of 6
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- ds007663
CrossModal Study
MEG# README ##Contact person [email protected], ORCID: https://orcid.org/0000-0002-3461-038X ## Overview #Project Name "CrossModal Study" ##Task Participants received cues to prepare for the target (auditory or visual). Between cue and target were 3 seconds of task-irrelevant waiting time. For the duration of this interval, the fixation cross was frequency-tagged at 36 Hz and an amplitude modulated 40 Hz tone was played. The target was either a gabor-patch or a short tone. Partic
- Participants
- 27
- Size
- 98.2 GB
- Updated
- Jun 6, 2026
- nm000229
Gwilliams et al. 2023 — Introducing MEG-MASC: a high-quality magneto-encephalography dataset for evaluating natural speech processing
ANAT MEGMEG-MASC is a high-quality magnetoencephalography dataset comprising raw MEG recordings from 27 English speakers listening to approximately two hours of naturalistic stories from the Manually Annotated Sub-Corpus (MASC). The dataset includes precise temporal annotations of word and phoneme onsets/offsets, organized according to the Brain Imaging Data Structure (BIDS) standard. This benchmark dataset enables large-scale encoding and decoding analyses of neural responses to natural speech processing, with accompanying code for validation analyses including temporal decoding of phonetic features and word frequency effects.
- Participants
- 27
- Size
- 99.3 GB
- Version
- v1.0.1
- Updated
- Jun 3, 2026
- ds007640
Dataset of emotion recognition using validated video stimuli with large-scale behavioral survey and MEG recordings
MEG BEH# Dataset of Emotion Recognition Using Validated Video Stimuli with Large-scale Behavioral Survey and MEG Recordings ## General Description This dataset was developed as part of research focused on brain signal-based emotion recognition by capturing high-fidelity Magnetoencephalography (MEG) signals during induced different emotional states. The dataset is organized into three primary components: 1. **Phenotype (Online Survey)**: Stored within the 'phenotype' directory, this component contain
- Participants
- 23
- Size
- 88.8 GB
- Updated
- Jun 6, 2026
- ds007524
LittlePrince_MEG_French_Read_Pallier2025
MEG MRI## Summary This dataset contains magnetoencephalography (MEG) recordings collected while participants read the French text of *Le Petit Prince* presented using a rapid serial visual presentation (RSVP) paradigm. A separate dataset containing MEG recordings from the auditory listening paradigm is available on OpenNeuro (accession number: ds007523). This data is analyzed in: d’Ascoli, S., Bel, C., Rapin, J. et al. Towards decoding individual words from non-invasive brain recordings. Nature Com
- Participants
- 50
- Size
- 299 GB
- Updated
- Jun 6, 2026
- ds007523
LPP MEG Listen
MEG MRI## Summary This dataset contains magnetoencephalography (MEG) recordings collected while participants listened to the French audiobook of *Le Petit Prince* by Antoine de Saint-Exupéry. A complementary MEG dataset from the same project, using a reading (RSVP) paradigm, is available on OpenNeuro (accession number: ds007524). This data is analyzed in: d’Ascoli, S., Bel, C., Rapin, J. et al. Towards decoding individual words from non-invasive brain recordings. Nature Communications 16, 10521 (20
- Participants
- 58
- Size
- 445 GB
- Updated
- Jun 6, 2026
- on003645
Face processing MEEG dataset with HED annotation
ANAT BEH EEG MEGImported from OpenNeuro ds003645
- Participants
- 18
- Size
- 54.5 GB
- Version
- v1.0.0
- Updated
- May 16, 2026
- on000117
Multisubject, multimodal face processing
ANAT BEH DWI FMAP FUNC MEGImported from OpenNeuro ds000117
- Participants
- 17
- Size
- 169 GB
- Version
- v1.0.0
- Updated
- May 18, 2026
- ds007353
HAD-MEEG
MEG EEG MRIHuman action recognition is a core component of social cognition, engaging spatially distributed and temporally evolving neural responses that encode visual information and infer intention. To map the brain’s spatial organization supporting this process, we previously released the Human Action Dataset (HAD), a functional magnetic resonance imaging (fMRI) resource. However, fMRI’s limited temporal resolution constrains its ability to capture rapid neural dynamics. Here, we present the HAD-MEEG da
- Participants
- 32
- Size
- 181 GB
- Updated
- Jun 6, 2026
- ds006720
Alpha power indexes working memory load for durations
MEG MRIThe data set contains anonymized raw magnetoencephalography (MEG) recordings of 23 healthy adult participants, performed at Neurospin, Gif sur Yvette, France. Participants performed an n-item delayed temporal reproduction task: They were presented with a sequence of one or three “empty” intervals (see cover figure), delimited by short pure tones. They had to maintain the sequence in memory (retention), and, upon a prompt, reproduce the whole sequence by pressing a button for each tone. Eight tas
- Participants
- 24
- Size
- 136 GB
- Updated
- Jun 6, 2026