on002312
OcularLDT
MEG
[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on002312-blue…
- Participants
- 19
- Size
- 35.0 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
Discover datasets
100 results for "semantic processing" · page 9 of 10 · ranked by relevance
-
- on004457
Electrical stimulation of temporal and limbic circuitry produces distinct responses in human ventral temporal cortex
iEEG…supported project R01 MH122258 "CRCNS: Processing speed in the human connectome across…
- Participants
- 5
- Citations
- 15
- Size
- 11.4 GB
- Version
- v1.0.0
- Updated
- Jul 10, 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
- nm000252
Imagined speech EEG dataset — long words condition (Nguyen et al. 2017)
EEGThis dataset comprises EEG recordings from 6 healthy participants performing imagined speech tasks involving two conditions: cooperate and independent word imagery. The study employed a motor imagery paradigm with auditory and visual cues, yielding 3,600 preprocessed trials (1,800 per class) recorded at 256 Hz from 64 channels. Data were analyzed using Riemannian manifold methods and relevance vector machines for brain-computer interface applications, achieving mean classification accuracy of 66.2±4.8%.
- Participants
- 6
- Channels
- 60 (10-10)
- Citations
- 97
- HED
- v8.4.0
- Size
- 1.27 GB
- Version
- v1.0.3
- Updated
- Aug 18, 2026
- nm000119
Oikonomou2016 – SSVEP MAMEM 1 dataset
EEG…False ## Signal Processing - **Classifiers**: LDA, SVM, Random Forest, kNN, Naive Bayes, CCA…
- Participants
- 11
- Channels
- 256 (egi-geodesic)
- Citations
- 40
- HED
- v8.4.0
- Size
- 11.4 GB
- Version
- v1.0.2
- Updated
- Aug 16, 2026
- on007058
Silent Visual Reading EEG
EEGThis dataset contains raw and processed EEG recordings from participants performing silent visual reading of naturalistic narrative stories, investigating auditory representations of words during silent reading. Data include BrainVision-format EEG recordings organized according to BIDS, along with derivative processed EEG signals, metadata linking sessions to stories and runs, and word-level feature embeddings.
- Participants
- 10
- Channels
- 63 (10-10)
- Size
- 35.3 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026
- on003620
Runabout: A mobile EEG study of auditory oddball processing in laboratory and real-world conditions
EEG…and environmental complexity on attentional processing (see below for experiment details). All…
- Participants
- 44
- Channels
- 35 (10-10)
- Citations
- 32
- Size
- 89.2 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- on004107
MIND DATA
ANAT MEGThis magnetoencephalography (MEG) dataset comprises neuroimaging data collected to establish standardized protocols for cross-site pooling of MEG data. The dataset demonstrates the application of BIDS formatting to MEG neuroimaging, facilitating data harmonization and reproducible analysis across multiple research institutions.
- Participants
- 9
- Citations
- 17
- Size
- 77.2 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- nm000120
Oikonomou2016 – SSVEP MAMEM 2 dataset
EEG…False ## Signal Processing - **Classifiers**: LDA, SVM, Random Forest, kNN, Naive Bayes, AdaBoost…
- Participants
- 11
- Channels
- 256 (egi-geodesic)
- Citations
- 38
- HED
- v8.4.0
- Size
- 9.72 GB
- Version
- v1.0.2
- Updated
- Aug 18, 2026
- on002908
Human MEG recordings during sequential conflict task
MEG[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on002908-blue…
- Participants
- 13
- Citations
- 1
- Size
- 58.3 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026