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on003766
A resource for assessing dynamic binary choices in the adult brain using EEG and mouse-tracking

BEH EEG Zarr

This dataset provides high-density (128-channel) EEG and mouse-tracking data from 31 adults aged 18-33, collected in 2020. It includes resting-state recordings and task recordings from food preference choices and semantic judgments. The resource is intended for studying the dynamic decision processes underlying binary choices in the human brain.

Participants

31

Channels

129 (egi-geodesic)

Citations

5

Size

153 GB

Version

v1.0.0

Updated

Jun 22, 2026

by Kun Chen et al. OpenNeuro ds003766
on005065
Heuristics in risky decision-making relate to preferential representation of information MEG data

MEG Zarr

MEG recordings from participants performing a localizer task and a risky decision-making task, used to study how heuristics in risky choice relate to preferential neural representation of information. The dataset includes raw MEG with photodiode-derived event timing, event information tables, and preprocessed epoched data for the localizer and choice phases.

Participants

21

Size

431 GB

Version

v1.0.0

Updated

Jun 26, 2026

by Evan M. Russek et al. OpenNeuro ds005065
on008446
Random and Sequential Order Finger Motor Imagery

EEG Zarr

EEG recordings from 20 participants performing a novel finger motor imagery paradigm in which cues for individual fingers were presented in random and sequential order blocks. The order of blocks was counterbalanced across participants. Data were acquired with a 65-channel g.tec system at 512 Hz and organized in BIDS format.

Participants

20

Channels

64 (10-10)

Size

30.6 GB

Version

v1.0.0

Updated

Sep 8, 2026

by Damm et al. OpenNeuro ds008446
nm000388
Training datasets for epilepsy analysis: sliding-window features derived from the Freiburg intracranial EEG database (Riccio et al. 2024), processed-data release

Modalities pending

This derivative dataset redistributes, unchanged, 20 per-patient feature tables computed from the Freiburg intracranial EEG database for epilepsy analysis. Each row is a 2-s sliding window (1-s step) with 1080 univariate and bivariate features, extracted from six electrodes (three in the epileptic focus, three outside it) across six frequency bands. Windows are labelled as pre-ictal, ictal, post-ictal or inter-ictal, so the tables can be used to train machine-learning models for seizure detection. No raw recordings are included.

Participants

20

Size

13.9 GB

Version

v1.0.0

Updated

Oct 8, 2026

by Christian Riccio et al.
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.
on004018
EEG recordings for 200 object images presented in RSVP sequences at 5Hz or 20Hz

EEG Zarr

EEG recordings from participants viewing 200 object images presented in rapid serial visual presentation (RSVP) streams at 5 Hz or 20 Hz. The dataset supports investigation of the temporal representational dynamics of visual object processing under rapid presentation conditions. It accompanies a published NeuroImage study on object representations in RSVP streams.

Participants

16

Citations

97

Size

10.6 GB

Version

v1.0.0

Updated

May 13, 2026

by Grootswagers et al. OpenNeuro ds004018
on004011
The nature of neural object representations during dynamic occlusion

MEG

Raw and preprocessed magnetoencephalography (MEG) recordings from participants viewing objects that moved along trajectories and were either occluded or disappeared. The dataset supports investigation of how the brain represents objects during dynamic occlusion. It includes behavioural and eye-tracking data as source data, and preprocessed epochs in CoSMoMVPA format.

Participants

22

Citations

12

Size

258 GB

Version

v1.0.0

Updated

Jun 18, 2026

by Lina Teichmann et al. OpenNeuro ds004011
on003825
Human electroencephalography recordings from 50 subjects for 22,248 images from 1,854 object concepts

EEG Zarr

Electroencephalography recordings from 50 participants viewing 22,248 images spanning 1,854 object concepts from the THINGS database. Images were shown in rapid serial visual presentation streams at 10 Hz while participants performed an orthogonal fixation colour change detection task. The dataset supports research on the temporal dynamics of object recognition and visual representation in the human brain.

Participants

50

Channels

63

Citations

3

Size

55.3 GB

Version

v1.0.0

Updated

Mar 14, 2026

by Grootswagers et al. OpenNeuro ds003825
on004388
Somatosensory evoked potentials in the human spinal cord to mixed nerve stimulation

EEG Zarr

This dataset contains simultaneous electroencephalography (EEG), electrospinography (ESG), electroneurography (ENG), and electromyography (EMG) recordings from 40 participants, together with electrocardiographic and respiratory signals. Four conditions were recorded: resting state with eyes open, mixed median nerve stimulation, mixed tibial nerve stimulation, and alternating median/tibial stimulation. ESG electrode positions are provided for each participant. The study was pre-registered on OSF.

Participants

40

Channels

64 (10-10)

Citations

2

Size

683 GB

Version

v1.0.0

Updated

Jun 24, 2026

by Birgit Nierula et al. OpenNeuro ds004388
nm000266
Sosulski et al. 2019 — Online Optimization of Stimulation Speed in an Auditory Brain-Computer Interface under Time Constraints

EEG Zarr

EEG recordings from 13 healthy participants performing an auditory oddball (P300) paradigm with target (1000 Hz) and non-target (500 Hz) tones at stimulus onset asynchronies between 60 and 600 ms. The study evaluated closed-loop Bayesian optimization and random search to find each individual's best stimulation speed for maximizing classification performance of a regularized LDA. The data comprise 31-channel EEG sampled at 1000 Hz, with an optimization part and a validation part.

Participants

13

Channels

31 (10-10)

Citations

2

HED

v8.4.0

Size

3.68 GB

Version

v1.0.7

Updated

Oct 9, 2026

by Jan Sosulski et al.