on006377
InclusionStudy
NIRS
[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on006377-blue…
- Participants
- 115
- Size
- 1.38 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
Discover datasets
100 results for "functional connectivity" · page 9 of 10 · ranked by relevance
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- on005863
Cognitive Electrophysiology in Socioeconomic Context in Adulthood
EEGThis dataset contains EEG recordings from 127 young adults (18-30 years) collected alongside measures of childhood and adulthood socioeconomic status (SES), including educational attainment, income, food security, and neighborhood characteristics. EEG tasks were drawn from or adapted from the ERP CORE resource, designed to elicit neural activity related to perception, cognition, and action. The dataset also includes an ADHD symptoms checklist, enabling investigation of relationships between SES, ADHD symptoms, and neural activity in a socioeconomically diverse adult sample.
- Participants
- 127
- Channels
- 27
- Citations
- 7
- Size
- 10.6 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026
- nm000336
Mainsah et al. 2025 — bigP3BCI: An Open, Diverse and Machine Learning Ready P300-based Brain-Computer Interface Dataset (Study R)
EEGBigP3BCI Study R is a P300-based brain-computer interface dataset comprising EEG recordings from 20 subjects performing a 9x8 multi-face character grid speller task across two sessions. This derivative dataset is part of the larger BigP3BCI collection, the largest public P300 BCI dataset with ~267 subjects across 20 studies. The data were acquired at 256 Hz using 32-channel EEG with a g.USBamp amplifier and are formatted according to BIDS standards with HED event annotations for standardized analysis and machine learning applications.
- Participants
- 20
- Channels
- 32 (10-10)
- HED
- v8.4.0
- Size
- 6.59 GB
- Version
- v1.0.3
- Updated
- Aug 18, 2026
- on003570
EEG: Improvisation and Musical Structures
EEG…a chord from a different functional class. For example, if the middle…
- Participants
- 40
- Channels
- 64 (10-10)
- Citations
- 41
- Size
- 36.1 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- on005127
AMRI 16-N-0031 sleep1
ANAT EEG FUNC[ recordings from 111 healthy control subjects acquired using a BioSemi ActiveTwo system with 64 electrodes. Subjects were recorded during four minutes of continuous EEG with eyes closed, with some subjects undergoing repeat recordings at a later timepoint. The dataset includes both raw EEG data rereferenced to average reference and a derived cleaned dataset preprocessed with an automated pipeline, along with demographic and cognitive test data.
- Participants
- 111
- Channels
- 64 (10-10)
- Citations
- 35
- Size
- 20.7 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- on006033
Synchronous EEG and fMRI dataset on inner speech
ANAT EEG FUNC…with TR=2s. ## Data Organization - Functional MRI data: `sub-xx/ses-xx…
- Participants
- 3
- Channels
- 64
- Citations
- 1
- Size
- 15.3 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026
- nm000303
Mainsah et al. 2025 — bigP3BCI: An Open, Diverse and Machine Learning Ready P300-based Brain-Computer Interface Dataset (Study O)
EEGBigP3BCI Study O is a P300-based brain-computer interface dataset comprising EEG recordings from 18 ALS subjects across 2 sessions each, using a 9x8 character grid with supervised and checkerboard stimulus paradigms. The dataset contains 32-channel EEG data sampled at 256 Hz with standardized 10-20 electrode montage, designed for machine learning applications in BCI speller systems. This derivative dataset is part of the larger BigP3BCI collection, the largest public P300 BCI dataset with recordings from approximately 267 subjects across 20 studies.
- Participants
- 18
- Channels
- 32 (10-10)
- HED
- v8.4.0
- Size
- 3.23 GB
- Version
- v1.0.3
- Updated
- Aug 18, 2026
- nm000191
BigP3BCI Study F — 6x6 multi-paradigm, 3 sessions (10 healthy subjects)
EEGBigP3BCI Study F is a derivative EEG dataset comprising P300-based brain-computer interface recordings from 10 ALS patients across 3 sessions using a 6x6 character grid speller paradigm. This dataset is extracted from the larger BigP3BCI benchmark (DOI: 10.13026/0byy-ry86) and processed using MOABB 1.5.0. The dataset contains 16-channel EEG data sampled at 256 Hz with visual stimulus presentations classified as target and non-target events, designed for evaluating P300 detection algorithms and BCI speller applications.
- Participants
- 10
- Channels
- 16 (10-10)
- HED
- v8.4.0
- Size
- 1.91 GB
- Version
- v1.0.2
- Updated
- Aug 18, 2026
- on004796
A Polish Electroencephalography, Alzheimer’s Risk-genes, Lifestyle and Neuroimaging (PEARL-Neuro) Database
EEG FUNC…ratio. * Neuroimaging data: * Functional data — electroencefalography (EEG) and functional magnetic resonance imaging…
- Participants
- 79
- Citations
- 36
- Size
- 240 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026