EEG data for observing the video stimuli

Published: 6 November 2019| Version 1 | DOI: 10.17632/s2dxrv45fr.1
Anatoly Bobe,
Dmitriy Fastovets,
Maria Komarova,
Grigory Rashkov,
Andrey Alekseev


This is EEG dataset collected within the research "Natural image reconstruction from brain waves: a novel visual BCI system with native feedback" Here we propose that observing visual stimuli of 5 different categories results in the different brain wave patterns decodable from noninvasive EEG. This hypothesis was tested on 17 subjects. All the data was collected by in autumn 2018, at MIPT Neurorobotics Lab, Dolgoprudny, Moscow Region, Russian Federation. The data was acquired using 128-channel MCS EEG Cap and NVX136 MCS amplifier, using NeoRec software provided by the manufacturer. The protocol included two sessions of the same video observing task. The video consisted of 117 different short clips, belonging to 5 different categories: abstract forms, waterfalls, faces, Goldberg mechanisms and speed. The clips were separated with black screen pauses of 2-3 seconds length. As for now, we cannot include the video itself due to copyright issues. We only provide screenshots of the video clips (except for category 2: faces). The detailed description can be found inside the ZIP archive.



Electroencephalography, Noninvasive Monitoring, Brain-Computer Interface