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on004483
ABSeqMEG

MEG Zarr

Magnetoencephalography (MEG) recordings from participants listening to 16-item binary sound sequences of varying complexity, used to test a language-of-thought account of compression in human working memory. Sequences were defined by minimal description length (transition probabilities, chunking, or nested structures), and occasional deviant sounds probed participants' knowledge of each sequence. The data accompany a study reporting that MEG and fMRI responses scale with sequence complexity.

Participants

19

Citations

26

Size

23.4 GB

Version

v1.0.0

Updated

Jun 24, 2026

by Samuel Planton* et al. OpenNeuro ds004483
on002761
memoryreplay

MEG Zarr

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on002761-blue…

Participants

25

Citations

14

Size

204 GB

Version

v1.0.0

Updated

Jun 21, 2026

by G. Elliott Wimmer et al. OpenNeuro ds002761
on005815
A Human EEG Dataset for Multisensory Perception and Mental Imagery

EEG Zarr

The YOTO (You Only Think Once) dataset is a human EEG resource for studying multisensory perception and mental imagery. Twenty participants completed tasks with unimodal and multimodal (visual, auditory, and combined) cues while EEG was recorded at 1000 Hz, and they gave self-reported vividness ratings of their imagery. Technical validation with event-related potentials and power spectral density analyses confirmed data reliability and distinct neural responses across stimuli, supporting research on neural decoding, perception, and cognitive modeling.

Participants

20

Channels

30

Size

9.91 GB

Version

v1.0.0

Updated

Jun 20, 2026

by Yan-Han Chang et al. OpenNeuro ds005815
on005095
STERNBERG DIFFICULT

EEG Zarr

…Participants were asked to recall whether the probe letter was in the…

Participants

48

Channels

63 (10-10)

Citations

2

Size

14.3 GB

Version

v1.0.0

Updated

Jun 26, 2026

by Natalia Zhozhikashvili et al. OpenNeuro ds005095
nm000199
Learning from label proportions for a visual matrix speller (ERP)

EEG Zarr

EEG recordings from 13 healthy participants performing a copy-spelling task with a visual 6x7 matrix ERP speller. The speller was designed for learning from label proportions (LLP), an unsupervised, calibrationless classification approach for ERP-based brain-computer interfaces. Two stimulus sequences with different target/non-target ratios allowed LLP to reconstruct mean target and non-target responses without labeled data. In the original online study, 84.5% of characters were spelled correctly on average without prior calibration.

Participants

13

Channels

31 (10-10)

Citations

46

HED

v8.4.0

Size

5.15 GB

Version

v1.0.3

Updated

Oct 8, 2026

by David Hübner et al.
on007964
Disentangling objects' contextual associations from perceptual and conceptual attributes using time-resolved neural decoding

EEG Zarr

Raw 128-channel EEG data from 20 observers viewing object images in a rapid presentation paradigm, together with representational dissimilarity matrices. The dataset supports time-resolved neural decoding analyses that separate objects' contextual associations from their perceptual and conceptual attributes. One participant was excluded because of a technical recording error, leaving 19 usable participants.

Participants

19

Citations

2

Size

18.9 GB

Version

v1.0.0

Updated

Jun 17, 2026

by Kim et al. OpenNeuro ds007964
nm000376
Intracranial EEG from 9 adults during a memory-guided actions experiment (preprocessed epochs, Moraresku et al.)

iEEG

…9–4.1 s), action/recall (2 s, green cross; joystick reach…

Participants

9

Size

12.9 GB

Version

v1.0.0

Updated

Oct 8, 2026

by Sofiia Moraresku et al.
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
on007162
Adaptive recruitment of cortex-wide recurrence for visual object recognition (EEG)

EEG Zarr

This dataset contains EEG recordings from 34 participants (one session each) who viewed 242 object images, 121 challenge and 121 control images, selected from comparisons between human behavioural performance and AlexNet. The study examines adaptive recruitment of cortex-wide recurrent processing during visual object recognition. The derivatives folder contains outputs of the decoding analyses, including time-resolved decoding accuracy matrices for object identity (.npz).

Participants

34

Channels

63 (10-10)

Citations

2

Size

61.2 GB

Version

v1.0.0

Updated

Jun 30, 2026

by [Unspecified1] et al. OpenNeuro ds007162
nm000374
Electrophysiological signatures underlying variability in human memory consolidation: raw intracranial EEG (learning and sleep TMR)

iEEG

Stereo-EEG depth recordings from 11 patients with medically refractory temporal lobe epilepsy, collected at Sanbo Brain Hospital in Beijing. Recordings cover learning of object-location associations and targeted memory reactivation (TMR) with sounds during NREM sleep. The data were used to study electrophysiological signatures of variability in human memory consolidation. They are re-packaged in iEEG-BIDS from the authors' Zenodo release without filtering, resampling or re-referencing.

Participants

11

Size

17.0 GB

Version

v1.0.0

Updated

Oct 8, 2026

by Wei Duan et al.