Discover datasets

TMNRED is a Chinese language EEG dataset comprising recordings from 30 healthy native speakers during natural reading tasks designed to investigate semantic processing mechanisms. Participants read text stimuli (15-20 characters) presented as news headlines or short sentences, with each participant completing 8 blocks of 400 trials. The dataset includes both raw and preprocessed EEG data organized according to BIDS standards. Sensor-level EEG analyses have been performed to examine neural responses to target and non-target semantic items.

Citations

1

Size

17.4 GB

Updated

Jun 26, 2026

…500-1000 ms fixation cross. Encoding (letter set), retention (blank screen), and…

Citations

1

Size

14.0 GB

Updated

Jun 26, 2026

This dataset contains preprocessed EEG recordings from 6 healthy participants performing imagined speech tasks with three short word conditions (out, in, up). Data were acquired at 256 Hz using 64 channels and analyzed using Riemannian manifold methods and relevance vector machines for brain-computer interface applications. The motor imagery paradigm employed auditory cueing, yielding 1,800 trials suitable for BCI research and benchmarking.

Size

379 MB

Updated

Jun 23, 2026

…Subsequently, each participant underwent 30 laser stimuli and provided verbal pain ratings…

Size

41.6 GB

Updated

Jun 18, 2026

…Subsequently, each participant underwent 30 laser stimulis and provided verbal pain ratings…

Size

19.4 GB

Updated

Jun 18, 2026

ChineseEEG is a high-density EEG dataset with simultaneous eye-tracking recordings from 10 participants silently reading Chinese novels for approximately 11 hours each. The dataset includes raw and preprocessed EEG data at multiple filtering levels, eye-tracking data, Chinese text materials from two novels (The Little Prince and Garnett Dream), and BERT-based Chinese text embeddings. This resource enables investigation of semantic alignment between neural representations and natural language processing model embeddings during Chinese language comprehension.

Citations

24

Size

696 GB

Updated

Jun 26, 2026

NeuroMorph is a high-temporal resolution magnetoencephalography (MEG) dataset comprising recordings from 24 subjects totaling over 17 hours of data acquired using a KIT/Yokogawa system with 208 magnetometer channels. The dataset is designed to support morpheme-based linguistic analysis and investigation of language and cognitive processes through visual presentation paradigms, providing a resource for studying neural mechanisms of language processing at fine temporal resolution.

Size

140 GB

Updated

Jun 26, 2026

…Disarming emotional memories using Targeted Memory Reactivation during Rapid Eye Movement sleep…

Size

6.47 GB

Updated

Jun 27, 2026

An EEG dataset of imagined speech from 15 healthy participants comparing traditional cue-based and gamified (Pac-Man maze) paradigms for brain-computer interface applications. The dataset comprises 1,800 trials across four Spanish directional commands recorded at 500 Hz from 24 electrodes using the mBrainTrain Smarting system. This derivative dataset enables systematic evaluation of paradigm design effects on imagined speech decoding performance.

Size

829 MB

Updated

Jun 22, 2026

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on004256-blue…

Size

18.2 GB

Updated

Jun 23, 2026