Discover datasets

# README ## Contact For additional information, please contact: Ethan R. Buch ([email protected]; ORCID: 0000-0002-5443-8222) ## Overview This study was carried out by the Human Cortical Physiology & Neurorehabilitation Section (HCPS) in the NINDS Intramural Research Program. The primary aim of the study was to investigate changes in brain activity associated with early skill learning during an initial training session, overnight skill consolidation and longer-term skill retention. A long

Participants

31

Size

95.8 GB

Updated

Jun 6, 2026

Participants

68

Size

64.1 GB

Updated

Jun 6, 2026

References ---------- Appelhoff, S., Sanderson, M., Brooks, T., Vliet, M., Quentin, R., Holdgraf, C., Chaumon, M., Mikulan, E., Tavabi, K., Höchenberger, R., Welke, D., Brunner, C., Rockhill, A., Larson, E., Gramfort, A. and Jas, M. (2019). MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis. Journal of Open Source Software 4: (1896).https://doi.org/10.21105/joss.01896 Niso, G., Gorgolewski, K. J., Bock, E., Brooks, T. L., Flandin, G., Gramfort, A

Participants

24

Size

102 GB

Updated

Jun 6, 2026

Overview This dataset, named 3M-CPSEED, consists of electroencephalogram (EEG) recordings obtained from 20 participants engaged in imagined speech tasks. 3M-CPSEED holds significant implications for speech neurophysiology research, not only facilitating exploration of neural activity differences across pinyin articulations but also enabling robust transfer learning studies for other alphabetic languages. Data Collection Participants: 20 healthy, right-handed individuals (average age: 24.55 ye

Participants

20

Size

8.17 GB

Updated

Jun 6, 2026

LIGHT Dataset During these guided imagery hypnotherapy sessions, a hypnotherapist integrates storytelling and deep visualizations techniques to encourage personal and wellbeing. This method allows individuals to explore and modify their subconscious narratives, in order to foster changes that resonate through their lives. This differs from traditional hypnotherapy by tapping into eudaemonic aspects of well-being, emphasizing the pursuit

Participants

9

Size

4.31 GB

Updated

Jun 6, 2026

Overview -------- This is the dataset for our study investigating the effects of selective attention to speech stimuli in the subcortex and cortex, entitled "The auditory brainstem response to natural speech is not affected by selective attention" by Stoll et al. (2025). Please cite our paper if you use our dataset. It contains EEG data for three experiments, detailed in the paper and briefly summarized below. Code and stimuli to derive the responses are provided in the Dataset folder and o

Participants

66

Size

103 GB

Updated

Jun 6, 2026

This is the dataset for Leong et al. (in prep). 33 participants completed both a visual and auditory surprise task in counterbalanced order. Methodological details are contained in the manuscript. Certain participants were excluded at various stages of the analyses. Their data and event lists are included up to the stage of processing that their data reached. Due to incorrect settings specific to OpenBCI GUI v5.0.1, indicated EEG values are 24 times larger than what they should be. The units

Participants

33

Size

535 MB

Updated

Jun 6, 2026

# BIDS example with HED-SCORE schema library annotations The HED schema library for the Standardized Computer-based Organized Reporting of EEG (SCORE) can be used to add annotations for BIDS datasets. The annotations are machine readable and validated with the BIDS and HED validators. This example is related to the following preprint: Dora Hermes, Tal Pal Attia, Sándor Beniczky, Jorge Bosch-Bayard, Arnaud Delorme, Brian Nils Lundstrom, Christine Rogers, Stefan Rampp, Seyed Yahya Shirazi, D

Participants

1

Size

32.0 MB

Updated

Jun 6, 2026

References ---------- Appelhoff, S., Sanderson, M., Brooks, T., Vliet, M., Quentin, R., Holdgraf, C., Chaumon, M., Mikulan, E., Tavabi, K., Höchenberger, R., Welke, D., Brunner, C., Rockhill, A., Larson, E., Gramfort, A. and Jas, M. (2019). MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis. Journal of Open Source Software 4: (1896). https://doi.org/10.21105/joss.01896 Pernet, C. R., Appelhoff, S., Gorgolewski, K. J., Flandin, G., Phillips, C., D

Participants

30

Size

23.0 GB

Updated

Jun 6, 2026

References ---------- Appelhoff, S., Sanderson, M., Brooks, T., Vliet, M., Quentin, R., Holdgraf, C., Chaumon, M., Mikulan, E., Tavabi, K., Höchenberger, R., Welke, D., Brunner, C., Rockhill, A., Larson, E., Gramfort, A. and Jas, M. (2019). MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis. Journal of Open Source Software 4: (1896). https://doi.org/10.21105/joss.01896 Pernet, C. R., Appelhoff, S., Gorgolewski, K. J., Flandin, G., Phillips, C., D

Participants

36

Size

31.1 GB

Updated

Jun 6, 2026