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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

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on006171-blue…

Participants

36

Channels

128 (10-05)

Citations

8

Size

67.8 GB

Version

v1.0.0

Updated

Jun 28, 2026

Magnetoencephalography (MEG) recordings from 50 healthy native French-speaking adults reading the French text of Le Petit Prince using a rapid serial visual presentation paradigm. The text was split into nine runs of about 8 minutes each. The dataset includes T1-weighted anatomical MRI, FreeSurfer reconstructions, and preprocessed MEG derivatives. It is intended for studying the neural basis of naturalistic reading and language comprehension.

Participants

50

Citations

39

Size

300 GB

Version

v1.0.0

Updated

Jun 14, 2026

…Pain Perception and Anxiety-Depression Levels](#2-pain-perception-and-anxiety-depression…

Participants

9

Channels

8

Size

1.75 GB

Version

v1.0.0

Updated

Jun 25, 2026

EEG dataset investigating anticipatory neural differences between attention and expectation. The recordings were collected by a research group led by Maria Ruz and are organized in BIDS format. The dataset is mirrored on NEMAR from OpenNeuro (ds004502).

Participants

48

Channels

65 (10-10)

Size

59.4 GB

Version

v1.0.0

Updated

Jun 24, 2026

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on003774-blue…

Participants

20

Channels

129 (egi-geodesic)

Citations

2

Size

10.1 GB

Version

v1.0.0

Updated

Jun 22, 2026

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

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on005107-blue…

Participants

21

Size

27.6 GB

Version

v1.0.0

Updated

Jun 26, 2026

The MNE-Sample-Data dataset is a simultaneous MEG and 60-channel EEG recording with an accompanying structural MRI, distributed with the MNE software. Checkerboard patterns were presented to the left and right visual fields, interleaved with tones to the left or right ear, and the subject responded to occasional smiley faces. It serves as a standard example dataset for demonstrating MEG/EEG analysis workflows, and FreeSurfer-derived anatomical surfaces are included.

Participants

2

Size

1.93 GB

Version

v1.0.0

Updated

Jun 20, 2026

High-density EEG recorded from resting, eyes-closed participants who used voice-guided imagery to enter 15 distinct emotional states, including positive states such as joy and negative states such as sadness and anger. Participants pressed a button when they began to feel the target emotion and again when the feeling waned, with relaxation instructions between the imagery periods. The dataset supports research on EEG-based emotion recognition and brain state dynamics during emotion imagination.

Participants

34

Channels

224 (biosemi)

Citations

73

Size

36.0 GB

Version

v1.0.0

Updated

Jun 21, 2026