What is this?

The GX Dataset is a dataset of combined tES, EEG, physiological, and behavioral signals from human subjects.

All aspects of this project are fully open source. If you are having access issues please contact us below.

 

Description

A dataset combining high-density electroencephalography (EEG) with physiological and continuous behavioral metrics during transcranial electrical stimulation (tES; including tDCS and tACS). Data includes within subject application of nine High-Definition tES (HD-tES) types targeted three brain regions (frontal, motor, parietal) with three waveforms (DC, 5Hz, 30Hz), with more than 783 total stimulation trials over 62 sessions with EEG, physiological (ECG or EKG, EOG), and continuous behavioral vigilance/alertness metrics (CTT task).

Publication

A full data descriptor is published in Nature Scientific DataPlease cite this work as:

Gebodh, N., Esmaeilpour, Z., Datta, A., Bikson, M. Dataset of concurrent EEG, ECG, and behavior with multiple doses of transcranial electrical stimulation. Sci Data 8, 274 (2021). https://doi.org/10.1038/s41597-021-01046-y
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Where can I download the data?

 

Where can I get the code for this work?

All the code used for this work can be accessed directly from this repository on Github.
Link text: https://github.com/ngebodh/GX_tES_EEG_Physio_Behavior

 

How to cite this work?

Thanks for exploring our dataset!
If you used any part of this project (data, figures, code, etc. ) please cite our published data descriptor and any appropriate repository.

PLEASE CITE DATA DESCRIPTOR AS:

Gebodh, N., Esmaeilpour, Z., Datta, A., Bikson, M. Dataset of concurrent EEG, ECG, and behavior with multiple doses of transcranial electrical stimulation. Sci Data 8, 274 (2021). https://doi.org/10.1038/s41597-021-01046-y Download citation ▼

 

Social Media

For the latest updates on this work and related topics feel free to follow @NigelGebodh on Twitter.

 

Acknowledgements

Portions of this study were funded by X (formerly Google X), the Moonshot Factory. The funding source had no influence on study conduction or result evaluation. MB is further supported by grants from the National Institutes of Health: R01NS101362, R01NS095123, R01NS112996, R01MH111896, R01MH109289, and (to NG) NIH-G-RISE T32GM136499. We would like to thank Yu Xin Zhu and Michaela Chum for all their technical assistance.


Questions?

If you have questions about any aspects of our dataset, or suggestions on improvements please let us know!