Discover datasets

EEG recordings from 54 healthy participants performing a 36-symbol ERP (P300) row-column speller task with face stimuli, collected over two sessions with offline training and online copy-spelling test phases. Data were recorded at 1000 Hz from 62 EEG channels plus 4 additional EMG channels. The dataset is part of a three-paradigm BCI collection (ERP, SSVEP, motor imagery) created to investigate BCI illiteracy and distributed with the OpenBMI toolbox.

Participants

54

Channels

62 (10-05)

Citations

100

HED

v8.4.0

Size

132 GB

Version

v1.0.5

Updated

Oct 8, 2026

…https://github.com/benjaminglowe/attribute-specific-prediction-error-analysis-code Please email…

Participants

37

Channels

64 (10-10)

Citations

3

Size

39.1 GB

Version

v1.0.0

Updated

Jun 25, 2026

…These predictions were upheld in both fMRI and MEG, indicating that sequence…

Participants

19

Citations

26

Size

23.4 GB

Version

v1.0.0

Updated

Jun 24, 2026

Clinical intracranial EEG (iEEG) recordings from 12 epilepsy surgery patients at the University Medical Center Utrecht, forming part of the RESPect (Registry for Epilepsy Surgery Patients) collection. Six patients were recorded intraoperatively with acute ECoG and six had long-term monitoring (three with ECoG, three with SEEG). The data are organized in BIDS, with separate session and run conventions for intraoperative and long-term recordings.

Participants

6

Size

2.60 GB

Version

v1.0.0

Updated

Jun 22, 2026

A clinical intracranial EEG (iEEG) dataset from 12 epilepsy surgery patients drawn from the RESPect (Registry for Epilepsy Surgery Patients) collection at the University Medical Center Utrecht. It includes six intraoperative ECoG recordings and six long-term recordings (three ECoG, three SEEG). The data are organized in BIDS, with session and run conventions that capture the surgical stage or the monitoring day and time, and the task labels describe the patient's state.

Participants

6

Citations

1

Size

99.3 GB

Version

v1.0.0

Updated

Jun 22, 2026

TX17 is an EEG dataset formatted according to BIDS with HED annotations, contributed by Johnson, Gordon, Touryan, and King. The README describes it only as a placeholder, so no further details on the experimental paradigm or participants are provided. It is a NEMAR-hosted copy of an OpenNeuro deposit.

Participants

1

Channels

64 (10-10)

HED

v8.1.0

Size

79.2 MB

Version

v1.0.0

Updated

May 13, 2026

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on005872-blue…

Participants

1

Channels

129 (egi-geodesic)

Citations

7

Size

43.6 MB

Version

v1.0.0

Updated

Jun 28, 2026

…Hierarchical structure guides rapid > linguistic predictions during naturalistic listening. *PLoS ONE*, 14…

Participants

45

Channels

60 (other)

Citations

91

Size

3.88 GB

Version

v1.1.3

Updated

Jul 3, 2026

EEG recordings from 20 healthy participants who wrote ten letters (a, d, e, f, j, n, o, s, t, v) with the right index finger after a visual cue. The dataset supports classification of handwritten characters, either directly from low-frequency and broadband EEG or with a two-step approach that first decodes continuous hand kinematics and then classifies the letter. It is intended for research on non-invasive brain-computer interfaces for communication.

Participants

20

Channels

60 (10-10)

Citations

13

HED

v8.4.0

Size

27.0 GB

Version

v1.0.2

Updated

Aug 18, 2026

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on006374-blue…

Participants

36

Channels

32 (10-10)

Size

42.7 GB

Version

v1.0.0

Updated

Jun 28, 2026