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nm000195
Mixture of LLP and EM for a visual matrix speller (ERP) dataset from

EEG Zarr

EEG recordings from an online brain-computer interface study with twelve healthy participants using a visual matrix P300 speller. Three fully unsupervised decoding methods were compared: learning from label proportions (LLP), expectation-maximization (EM), and their mixture (MIX). Participants copy-spelled a German sentence across three blocks, one per algorithm. The dataset supports research on calibration-free ERP-based BCIs.

Participants

12

Channels

31 (10-10)

Citations

27

HED

v8.4.0

Size

4.81 GB

Version

v1.0.3

Updated

Oct 8, 2026

by David Hübner et al.
nm000368
Sternberg working memory: human microwire LFP from medial temporal and medial frontal lobe (Daume et al. 2024, DANDI 000673)

iEEG

Microwire local field potentials (400 Hz) from Behnke-Fried hybrid depth electrodes in 35 patients with drug-resistant epilepsy, recorded during a picture-based Sternberg working-memory task with load 1 or load 3. Recording sites include the hippocampus, amygdala, dorsal anterior cingulate cortex, pre-supplementary motor area and ventromedial prefrontal cortex. This is an iEEG-BIDS representation of the NWB data released on DANDI (000673) from the Daume et al. 2024 study, with signal values unchanged.

Participants

35

Size

4.11 GB

Version

v1.0.0

Updated

Oct 8, 2026

by Jonathan Daume et al.
on002725
A dataset recording joint EEG-fMRI during affective music listening

ANAT EEG FUNC Zarr

Joint EEG-fMRI recordings from 21 healthy adults who listened to music stimuli chosen and generated to evoke different affective responses. Participants self-reported their felt affective states during listening. The dataset supports research on the neural correlates of emotional responses to music, including sub-cortical activity reflected in EEG.

Participants

21

Channels

31 (10-10)

Size

15.3 GB

Version

v1.0.0

Updated

Jun 21, 2026

by Ian Daly et al. OpenNeuro ds002725
on004457
Electrical stimulation of temporal and limbic circuitry produces distinct responses in human ventral temporal cortex

iEEG Zarr

Intracranial EEG recordings from five patients undergoing clinical monitoring at the Mayo Clinic, collected during single pulse electrical stimulation. The dataset supports identification of distinct basis profile curves in human ventral temporal cortex evoked by stimulation of temporal and limbic circuitry. Analysis code is available in an accompanying GitHub repository.

Participants

5

Citations

18

Size

11.4 GB

Version

v1.0.0

Updated

Jun 24, 2026

by Harvey Huang et al. OpenNeuro ds004457
nm000253
Wang et al. 2024 — Brain Treebank: Large-scale intracranial recordings from naturalistic language stimuli

iEEG Zarr

The Brain Treebank is a large-scale dataset of intracranial (stereo-EEG) recordings from 10 epilepsy patients who watched Hollywood movies. Signals were sampled at 2048 Hz from 1,688 electrodes in total, across 26 movie trials and about 43 hours of data. The movie audio was transcribed with manually annotated word onsets, and each transcript was parsed into Universal Dependencies syntax trees. This makes the dataset a resource for studying the neural basis of naturalistic language. This record provides the data in BIDS-iEEG format.

Participants

10

Size

257 GB

Version

v1.1.0

Updated

Sep 21, 2026

by Christopher Wang et al.
nm000311
Multimodal upper-limb MI/ME EEG (Jeong et al. 2020)

EEG Zarr

A multimodal EEG, EOG and EMG dataset from 25 healthy, BCI-naive right-handed participants performing motor imagery and real movement of 11 intuitive upper-limb tasks. The tasks were 6 reaching directions, 3 grasping types and 2 wrist-twisting movements. Each participant completed 3 sessions of 550 trials. Recordings used 60 EEG channels at 1000 Hz. This BIDS derivative was generated via MOABB and is intended for BCI research on motor control and prosthetics.

Participants

25

Channels

71 (10-10)

Citations

87

HED

v8.4.0

Size

326 GB

Version

v1.0.2

Updated

Aug 18, 2026

by Ji-Hoon Jeong et al.
on008465
NeuralEcho MACS high-density communication-related EEG dataset

EEG Zarr

High-density (127-channel) EEG recordings from 30 healthy, right-handed, native Chinese-speaking adults performing imagined and executed vocalization and writing tasks. Stimuli were four Chinese strokes (heng, shu, pie, na) and four English letters (a, b, c, d). The factorial design crossed task mode, action, script and token identity, yielding 32 event-coded conditions and 15,360 task events. The release also includes EEGLAB preprocessing derivatives and subject-level machine-learning exports.

Participants

30

Channels

124 (10-05)

Size

181 GB

Version

v1.0.0

Updated

Sep 8, 2026

by Huang Jinfeng et al. OpenNeuro ds008465
nm000178
BNCI 2020-001 Reach-and-Grasp Electrode Comparison EEG dataset

EEG Zarr

EEG recordings from healthy participants performing self-initiated palmar and lateral reach-and-grasp actions, acquired simultaneously across three recording systems: gel-based laboratory EEG, water-based mobile EEG, and dry-electrode mobile EEG. The dataset supports investigation of the feasibility of decoding natural reach-and-grasp movement-related cortical potentials across EEG acquisition modalities for brain-computer interface applications. It is distributed in BIDS format as part of the MOABB benchmark collection.

Participants

45

Channels

58 (10-05)

Citations

50

HED

v8.4.0

Size

8.67 GB

Version

v1.0.4

Updated

Oct 8, 2026

by Andreas Schwarz et al.