Discover datasets

This dataset contains EEG/ERP data from an experiment examining sensitivity to semantic and syntactic violations in deaf readers. Participants read sentences presented word-by-word (RSVP) that contained subject-verb agreement violations, semantic violations, combined violations, word-order violations, or correct control sentences, while EEG was recorded. The study aims to characterize how deaf readers process linguistic anomalies at the neural level.

Participants

62

Channels

32 (10-10)

Citations

2

Size

8.53 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset contains EEG recordings from participants undergoing laser-evoked pain stimulation at four individually calibrated intensity levels, applied to the left and right hand dorsum. Participants rated perceived pain intensity using a numerical rating scale (0-10) following each stimulus, across 80 trials in a two-factor repeated-measures within-subject design. The dataset supports research into the neural correlates of pain perception and intensity coding.

Participants

95

Channels

60 (10-10)

Size

300 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset contains EEG recordings collected as part of the UV_EEG study by Yukako Ito, mirrored on NEMAR from the original OpenNeuro repository. It provides electrophysiological data intended for reuse in EEG research, following BIDS standards for data organization.

Participants

22

Channels

6 (10-10)

Citations

5

Size

71.9 MB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset investigates the neural representation of consciously seen and unseen information, likely using EEG recordings to examine visual consciousness and perception. It is designed to support research into the neural correlates of conscious versus unconscious processing of visual stimuli.

Participants

33

Channels

63 (10-10)

Citations

1

Size

44.4 GB

Version

v1.0.0

Updated

Aug 19, 2026

NeuroMorph is a high-temporal resolution MEG dataset designed for morpheme-based linguistic analysis, comprising recordings from 24 subjects totaling over 17 hours of data. Data were collected using a KIT/Yokogawa MEG system to investigate visual language and cognitive processing, with a focus on morphological structure in written language comprehension.

Participants

24

Size

140 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset comprises overnight sleep EEG recordings from 20 healthy participants, collected in spring 2017 as part of a wearable sleep monitoring study at the Surrey Clinical Research Centre. Recordings include full polysomnography (PSG) and around-the-ear cEEGrid measurements, with most subjects having both modalities recorded on the same night. The dataset supports comparison between conventional PSG and wearable cEEGrid sleep staging approaches.

Participants

20

Channels

6 (other)

Citations

94

Size

69.1 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset contains EEG and eye-tracking recordings from 30 participants who searched for objects in naturalistic scenes and intentionally memorized others, followed by a surprise recognition memory test. The study examines the 'search superiority effect,' testing whether incidentally encoded memories differ qualitatively from intentional ones through recollection and familiarity processes indexed by FN400 and late parietal ERP components. Behavioral remember-know judgments and ROC analyses were used alongside EEG measures to disentangle these memory processes.

Participants

30

Channels

61

Citations

1

Size

17.0 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset comprises multi-night ear-EEG and polysomnography (PSG) recordings collected between 2018 and 2020 to develop and validate ear-EEG as a home-based sleep monitoring platform. Twenty subjects were recorded across four nights with partial PSG, ear-EEG, and actigraphy, while ten of these subjects continued for an additional twelve nights using only ear-EEG, actigraphy, and a single EOG electrode. Supplementary behavioral data include nightly comfort questionnaires, sleep diaries, and actigraphy recordings, providing a rich resource for studying sleep physiology and wearable EEG signal quality.

Participants

20

Citations

98

Size

783 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset comprises overnight ear-EEG recordings from 10 healthy participants, collected between 2020 and 2022 as part of a study on ear-EEG based sleep monitoring. The first two recordings include simultaneous polysomnography (PSG) and ear-EEG measurements, while subsequent nights consist solely of ear-EEG recordings performed at the subjects' homes. The dataset is intended to support development and validation of ear-EEG as a wearable alternative to traditional PSG for sleep staging and monitoring.

Participants

10

Channels

8 (10-20)

Citations

2

Size

88.6 GB

Version

v1.0.0

Updated

Aug 19, 2026

Chisco is a Chinese imagined speech EEG dataset collected from five participants, each recorded over 5-6 sessions. The dataset includes raw EEG recordings and preprocessed data (in fif and pkl formats), along with accompanying text stimuli used to elicit imagined speech. It is intended to support research on imagined speech decoding and brain-computer interface applications using EEG signals.

Participants

5

Size

262 GB

Version

v1.0.0

Updated

Aug 19, 2026