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ROAMM is a large-scale multimodal dataset combining simultaneous EEG and eye-tracking recordings collected during naturalistic reading, with span-level mind-wandering annotations from 44 participants. It provides a benchmark for mind-wandering detection and EEG-to-text decoding, supporting research on attention-related degradation in language decoding from brain activity during naturalistic reading.

Participants

1

Channels

64 (10-10)

Citations

2

Size

46.6 GB

Version

v1.0.0

Updated

Aug 18, 2026

…Oddball task: Standing / Walking alone / Walking together. Participants performed an oddball task…

Participants

18

Channels

64 (10-05)

Citations

1

Size

19.8 GB

Version

v1.0.0

Updated

Jul 10, 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

Aug 19, 2026

…microgravity condition with distinct acquisition setup # Motor Imagery Tasks Tasks include: Left…

Participants

84

Channels

69 (10-10)

Citations

2

Size

144 GB

Version

v1.0.0

Updated

Aug 18, 2026

This dataset contains EEG recordings from an experiment in which participants alternately perceived and imagined visual images based on auditory prompts. Each trial consisted of a 6-second perception phase, during which participants viewed an image, followed by a 6-second imagination phase with eyes closed. The dataset is intended to support research on EEG-based analysis of perception and mental imagery processes, such as deep learning approaches to EEG decoding.

Participants

3

Channels

65 (10-10)

Size

4.23 GB

Version

v1.0.0

Updated

Aug 19, 2026

…The driving practice task lasted 10-15 min, until asymptotic performance in…

Participants

21

Channels

64 (10-10)

Citations

32

HED

v8.0.0

Size

23.9 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset contains EEG recordings from 34 participants collected to investigate the adaptive recruitment of cortex-wide recurrent processing during visual object recognition. Participants viewed a stimulus set of 242 images, comprising 'challenge' and 'control' images selected based on discrepancies between human behavioral performance and AlexNet classification, while performing a rapid serial visual presentation task with a paper-clip detection component. The dataset includes derivatives with time-resolved decoding accuracy matrices for object identity, supporting analyses of recurrent cortical dynamics in visual processing.

Participants

34

Channels

63 (10-10)

Citations

1

Size

61.2 GB

Version

v1.0.0

Updated

Aug 19, 2026

…the main instruction-following task and an additional localizer task. The data…

Participants

41

Channels

63 (10-10)

Citations

5

Size

57.7 GB

Version

v1.0.0

Updated

Aug 19, 2026

…Runs 1-3 (1-5 for subject 1) are the localizer task…

Participants

21

Size

431 GB

Version

v1.0.0

Updated

Aug 19, 2026

…rest or task (Rest, Task-ME, Task-MI, Task-NF) - ''stim_file…

Participants

10

Size

18.0 GB

Version

v1.0.0

Updated

Jul 10, 2026