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This MEG dataset comprises auditory cortex mapping data from a single subject acquired using a CTF 275 system at 120 kHz sampling rate. The experiment involved passive listening to 1,795 iso-intensity pure tones ranging from 100 Hz to 21.5 kHz presented binaurally over a 12-minute acquisition run. The dataset includes anatomical MRI data processed with FreeSurfer and serves as a reference example for MEG-based auditory cortex mapping techniques.

Participants

2

Size

15.5 GB

Version

v1.0.0

Updated

Jul 10, 2026

A comprehensive EEG dataset comprising 54 healthy subjects performing three major brain-computer interface (BCI) paradigms—motor imagery, event-related potentials, and steady-state visually evoked potentials—across two sessions. The dataset investigates BCI illiteracy rates and performance variations, revealing that motor imagery exhibits the highest illiteracy rate (53.7%) compared to other paradigms, while all participants demonstrated proficiency with at least one BCI system.

Participants

23

Channels

62 (10-05)

Citations

98

HED

v8.4.0

Size

60.8 GB

Version

v1.0.1

Updated

Jul 10, 2026

FLUX is a comprehensive pipeline for magnetoencephalography (MEG) data analysis, providing standardized workflows for processing and analyzing MEG recordings. This dataset demonstrates the application of the FLUX pipeline to MEG neuroimaging data organized according to the Brain Imaging Data Structure (BIDS) standard, facilitating reproducible and transparent MEG analysis across research groups. The dataset is derived from OpenNeuro ds004346 and contains MEG recordings with anatomical data.

Participants

1

Size

15.0 GB

Version

v1.0.0

Updated

Jul 10, 2026

A magnetoencephalography dataset from 13 participants performing audiovisual multisensory tasks, including causality judgment, temporal order judgment, and unimodal localizer conditions. The dataset comprises 1500 trials of audiovisual sequences with simultaneous behavioral recordings and structural MRI, designed to investigate neural mechanisms of multisensory correlation computations using time-resolved encoding models.

Participants

14

Size

75.1 GB

Version

v1.0.0

Updated

Jul 10, 2026

BigP3BCI Study Q is a P300-based brain-computer interface dataset comprising EEG recordings from 36 ALS subjects across 3 sessions each, using a 6x6 color intensification speller paradigm. The dataset contains 32-channel EEG data sampled at 256 Hz with standardized 10-20 electrode montage, annotated with target and non-target event labels for machine learning applications. 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

36

Channels

32 (10-10)

HED

v8.4.0

Size

1.09 GB

Version

v1.0.1

Updated

Jul 10, 2026