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This dataset comprises simultaneous EEG-fMRI recordings from 24 healthy adults performing a sustained attention task (GradCPT) and a resting-state task with intermittent multi-dimensional experience sampling, collected across two sessions per participant. It includes behavioral responses, experience sampling ratings across 13 dimensions of thought, and mental health survey data, enabling study of the neural correlates of attentional fluctuations, mind-wandering, and the reliability of EEG-fMRI relationships across sessions.

Participants

24

Channels

31 (10-10)

Citations

1

Size

115 GB

Version

v1.0.0

Updated

Aug 18, 2026

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on004584-blue…

Participants

149

Channels

63 (10-10)

Citations

14

Size

2.87 GB

Version

v1.0.0

Updated

Jul 10, 2026

This 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

…Nine-class auditory ERP paradigm with predictive text entry system (PASS2D). Users…

Participants

10

Channels

63 (10-10)

Citations

84

HED

v8.4.0

Size

7.62 GB

Version

v1.0.2

Updated

Aug 18, 2026

BigP3BCI Study J is a P300-based brain-computer interface dataset comprising EEG recordings from 20 healthy subjects performing a 9x8 character grid speller task. 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 16-channel EEG with a g.USBamp amplifier and include target and non-target event classifications suitable for machine learning applications.

Participants

20

Channels

16 (10-10)

HED

v8.4.0

Size

1.49 GB

Version

v1.0.3

Updated

Aug 18, 2026

…EEG are promising non-invasive biomarkers of epileptogenicity. However, it is unclear…

Participants

30

Channels

23 (10-20)

Citations

6

Size

28.3 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises intracranial EEG recordings and behavioral events from a categorized free recall task with closed-loop electrical stimulation applied during encoding. Participants studied word lists organized by semantic category, performed arithmetic distractor tasks, and freely recalled words, while a classifier trained on prior encoding data determined stimulation delivery based on predicted memory encoding success. Data were collected across multiple clinical sites in collaboration with the Computational Memory Lab at the University of Pennsylvania, as part of the DARPA Restoring Active Memory (RAM) project.

Participants

9

Size

12.2 GB

Version

v1.0.0

Updated

Aug 19, 2026

BigP3BCI Study C is a P300-based brain-computer interface dataset comprising EEG recordings from 19 healthy subjects performing a visual speller task using a 6x6 checkerboard paradigm. The dataset contains single-session recordings with 32-channel EEG data sampled at 256 Hz, annotated with target and non-target event labels. This derivative dataset is part of the larger BigP3BCI collection, the largest public P300 BCI dataset, and is formatted according to BIDS standards with HED event annotations for machine learning applications.

Participants

19

Channels

32 (10-10)

HED

v8.4.0

Size

4.11 GB

Version

v1.0.3

Updated

Aug 18, 2026

…MPF features + LSTM ## Key Findings - **Predictive signals**: sEMG precedes movement by tens…

Participants

100

Size

24.9 GB

Version

v2.0.0

Updated

Jul 10, 2026

A 32-channel EEG dataset from 12 healthy subjects performing a spatial navigation task using a single-flicker steady-state visual evoked potential (SSVEP) brain-computer interface. The dataset comprises two sessions per subject: a structured training session with 200 trials per subject recorded at 2048 Hz, and an online adaptive BCI game session recorded at 512 Hz. This paradigm employs a spatially-coded approach where a single 15 Hz flickering stimulus in the center of the screen produces distinct spatial topographies corresponding to four cardinal directions (north, east, west, south), enabling direction-specific decoding without frequency-based analysis methods.

Participants

12

Channels

32 (10-10)

Citations

52

HED

v8.4.0

Size

10.9 GB

Version

v1.0.2

Updated

Aug 18, 2026