Discover datasets

This dataset, titled Expectation of Conflict Stimuli, accompanies a study of how the brain forms expectations about upcoming conflict and adapts to it. It is associated with research on the role of lateral prefrontal theta oscillations in a computational mechanism underlying conflict expectation and adaptation. The dataset is organized in BIDS format and mirrored on NEMAR from OpenNeuro.

Participants

29

Channels

66 (10-10)

Citations

8

Size

63.3 GB

Version

v1.0.0

Updated

Jun 27, 2026

EEG recordings from 24 healthy participants performing a visual oddball (P300) event-related potential paradigm during mobile conditions: standing, walking, and running. Data were acquired with scalp and ear-EEG systems (73 channels, plus EOG) across five sessions per participant. This is a BIDS-formatted derivative of the Mobile BCI dataset, intended for benchmarking brain-computer interface decoding under locomotion.

Participants

24

Channels

48 (10-10)

Citations

36

HED

v8.4.0

Size

8.08 GB

Version

v1.0.3

Updated

Oct 8, 2026

This dataset contains EEG recordings from phoneme discrimination tasks combined with transcranial magnetic stimulation (TMS) of the motor cortex. It merges two studies: a 2019 study of consonant-vowel and vowel-consonant pairs in 8 participants, and a 2021 study in 16 participants that added single phonemes, real words and pseudowords. It is intended to support research on speech decoding and the role of articulation and coarticulation in speech perception.

Participants

24

Channels

61 (10-10)

Size

83.8 GB

Version

v1.0.0

Updated

Jun 28, 2026

NeuroMorph is a magnetoencephalography (MEG) dataset with high temporal resolution, designed for morpheme-based linguistic analysis. It contains recordings from 24 participants, totaling over 17 hours of data, acquired with a 208-channel KIT/Yokogawa magnetometer system. The dataset supports research on the neural processing of morphology during language comprehension.

Participants

24

Size

140 GB

Version

v1.0.0

Updated

Jun 26, 2026

This dataset contains magnetoencephalography (MEG) recordings from participants performing a cued recall task involving personally familiar people and places. It was collected to examine sustained neural representations of familiar people and places during recall. The data are organized in BIDS format.

Participants

30

Size

76.7 GB

Version

v1.0.0

Updated

Jun 23, 2026

Alljoined-1.6M is a large-scale EEG dataset of neural responses to rapid serial visual presentation of natural images from the THINGS database. It was recorded with a consumer-grade 32-channel EMOTIV FLEX2 system in 20 adult participants over four sessions each, yielding more than 1.6 million trials. The dataset was built to test whether deep-learning-based brain-computer interface and semantic decoding research can be done with affordable EEG hardware.

Participants

20

Channels

32 (10-10)

Size

8.78 GB

Version

v1.0.3

Updated

Sep 23, 2026

EEG dataset from a cross-modal cueing study in which participants were cued to prepare for an auditory, visual, or non-specific target. A 3-second task-irrelevant delay followed the cue, during which a fixation cross was frequency-tagged at 36 Hz and a 40 Hz amplitude-modulated tone was played. Participants discriminated one of three gabor-patch or tone targets, sometimes with a distractor from the uncued modality. The dataset supports investigation of alpha oscillations and target preparation in cross-modal attention.

Participants

22

Channels

63 (10-10)

Citations

2

Size

7.18 GB

Version

v1.0.0

Updated

Jun 30, 2026

This dataset provides simultaneous EEG and fNIRS recordings from 12 participants performing a silent naming task and three sensory-based imagery tasks (visual, auditory, tactile) on objects from the semantic categories of animals and tools. It supports research on semantic decoding and brain-computer interfacing. Stimulus images and example Python scripts for loading the data with MNE and MNE-BIDS are included.

Participants

12

Channels

64 (biosemi)

Citations

11

Size

24.2 GB

Version

v1.0.0

Updated

Jun 24, 2026

A multi-modal face processing dataset combining simultaneously recorded MEG and EEG with structural MRI from 18 participants. Participants viewed famous, unfamiliar, and scrambled faces and made a symmetry judgment by button press. The data are a curated repackaging of the MEEG portion of ds000117, with reorganized event logs, Hierarchical Event Descriptor (HED) annotations, and EEGLAB-format EEG.

Participants

19

Citations

80

HED

v8.1.0

Size

106 GB

Version

v1.0.0

Updated

Mar 9, 2026

EEG dataset investigating the neural representation of consciously seen and unseen information. The recordings were collected by Rodríguez-San Esteban, Chica, and González-López and are shared in BIDS format. The dataset is mirrored on NEMAR from OpenNeuro (ds005273).

Participants

33

Channels

63 (10-10)

Size

44.4 GB

Version

v1.0.0

Updated

Jun 26, 2026