Discover datasets

VEPCON is a multimodal neuroimaging dataset comprising high-density EEG, structural MRI, and diffusion-weighted imaging from 20 participants performing visual discrimination tasks (face vs. scrambled faces, coherent vs. incoherent motion). The dataset includes preprocessed EEG single trials, individual brain parcellations at five spatial resolutions, structural connectomes derived from diffusion data, and EEG source imaging solutions based on individual anatomy. This resource supports multimodal methods development, structure-function relationship studies, and optimization of source imaging and graph analysis techniques.

Participants

20

Channels

128 (biosemi)

Citations

24

Size

58.2 GB

Version

v1.0.0

Updated

Jul 22, 2026

…Dynamic Causal Tractography Analysis of Auditory Descriptive Naming: An Intracranial Study of…

Participants

106

Citations

2

Size

40.0 GB

Version

v1.0.0

Updated

Aug 19, 2026

A synchronized multimodal neuroimaging dataset containing concurrent fMRI and MEG recordings from 12 Mandarin Chinese speakers during naturalistic story listening, supplemented with high-resolution structural imaging, diffusion MRI, and resting-state fMRI. The dataset includes rich linguistic annotations of stimuli encompassing word frequencies, syntactic structures, temporal alignments, and embeddings from multiple pre-trained language models, enabling comprehensive investigation of neural mechanisms underlying language processing.

Participants

12

Citations

6

Size

1.36 TB

Version

v1.0.0

Updated

Jul 22, 2026

A multimodal neuroimaging dataset combining EEG, eye-tracking, and high-speed video recordings from 31 healthy participants performing motor imagery tasks. The dataset comprises 2,520 trials across 63 sessions, with participants performing left and right hand motor imagery in response to visual cues. Recorded at 1000 Hz using a 64-channel EEG montage with standardized electrode placement, this dataset supports brain-computer interface research and analysis of ocular activity patterns during motor imagery paradigms.

Participants

31

Channels

62 (10-10)

Citations

11

HED

v8.4.0

Size

33.6 GB

Version

v1.0.3

Updated

Aug 18, 2026

NeuroMorph is a high-temporal resolution MEG dataset designed for morpheme-based linguistic analysis, comprising recordings from 24 subjects totaling over 17 hours of data. Data were collected using a KIT/Yokogawa MEG system to investigate visual language and cognitive processing, with a focus on morphological structure in written language comprehension.

Participants

24

Size

140 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset comprises neuroimaging data from 8 participants performing functional localizer and movie-viewing tasks acquired simultaneously using Very High Density Diffuse Optical Tomography (VHD-DOT) and functional MRI. The dataset includes raw VHD-DOT data in SNIRF format from sessions 1-2 and fMRI data in NIfTI format from session 3 onwards, with preprocessed fMRI derivatives provided for direct comparison with optical neuroimaging measurements. Published in Imaging Neuroscience (2025).

Participants

8

Size

237 GB

Version

v1.0.0

Updated

Jul 10, 2026

Imported from OpenNeuro ds007181

Participants

66

Channels

19 (other)

Size

59.2 GB

Version

v1.0.0

Updated

Jul 10, 2026