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TX15 is a BIDS-formatted EEG dataset (BIDS version 1.8.0) with HED (Hierarchical Event Descriptors) version 8.1.0 annotations. The dataset includes EEG recordings and associated metadata in standardized formats (.set, .fdt, .tsv, .json). This dataset is derived from OpenNeuro dataset ds004842 (v1.0.0) and has been processed and annotated with HED tags to support standardized neuroimaging research. Released under the CC0 license, this dataset is made openly available to support reproducible science and neuroimaging research.

Participants

14

Channels

64 (10-10)

Citations

2

HED

v8.1.0

Size

5.21 GB

Version

v1.0.0

Updated

Jul 10, 2026

…XX/ses-YY/eeg/sub-XX_ses-YY_space-CapTrak_coordsystem.json…

Participants

20

Channels

32 (10-10)

Citations

1

Size

7.75 GB

Version

v1.0.0

Updated

Jul 10, 2026

A high-gamma EEG dataset comprising 14 healthy subjects performing motor imagery tasks (left hand, right hand, feet, and rest) recorded at 500 Hz with 128 channels. This is a BIDS-formatted derivative of the original dataset described in Schirrmeister et al. 2017, which was used to develop and validate deep convolutional neural networks for end-to-end EEG decoding. The derivative demonstrates that deep learning approaches can match or exceed traditional feature-based methods (FBCSP) while learning interpretable spectral power modulations in alpha, beta, and high-gamma frequency bands.

Participants

14

Channels

128 (10-05)

Citations

76

HED

v8.4.0

Size

31.3 GB

Version

v1.0.3

Updated

Aug 18, 2026

…types**: eeg=31, eog=2 - **Montage**: standard_1005 - **Hardware**: eego mylab (ANT…

Participants

8

Channels

31 (10-10)

Citations

3

HED

v8.4.0

Size

5.30 GB

Version

v1.0.2

Updated

Aug 18, 2026

This dataset comprises electroencephalographic recordings from 32 participants performing motor imagery tasks during sit-to-stand and stand-to-sit transitions in both offline and online brain-computer interface (BCI) paradigms. Participants completed guided motor imagery trials while seated or standing, with EEG signals recorded from 17 channels at 250 Hz. The dataset includes offline calibration phases used to train machine learning classifiers and corresponding online validation phases where real-time BCI decoding was performed, providing a comprehensive resource for investigating neural correlates of postural transitions and BCI performance.

Participants

32

Channels

17 (10-10)

Size

2.03 GB

Version

v1.0.0

Updated

Jul 10, 2026

…on006593) # Multimodal Sensor Fusion for EEG-Based BCI Typing Systems ## Dataset Overview…

Participants

21

Channels

19 (10-20)

Size

616 MB

Version

v1.0.0

Updated

Aug 19, 2026

Imported from OpenNeuro ds004368

Participants

39

Channels

63 (10-10)

Size

969 MB

Version

v1.0.0

Updated

Jul 10, 2026

…The EEG was recorded with an active 64 channel HIamp EEG amplifier…

Participants

14

Channels

64 (10-10)

Size

10.1 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset contains laser-evoked potential recordings capturing neural responses in the human spinal cord and cortex following nociceptive laser stimulation. It was collected to investigate the neurophysiological processing of pain-related signals across spinal and cortical levels. The dataset is organized according to the BIDS standard for electrophysiological data.

Participants

7

Channels

72 (other)

Size

18.6 GB

Version

v1.0.0

Updated

Aug 19, 2026

…solutions, noise covariance matrices, source spaces, transformation files, evoked data, and source…

Participants

50

Citations

29

Size

299 GB

Version

v1.0.0

Updated

Jul 10, 2026