Synthetic and real EEG datasets for closed-loop neuroscience
Authors/Creators
Description
The dataset is made primarily for the task of real-time low latency filtering of the EEG data in the closed loop neuroscience experiments and for EEG forecasting task. The dataset consists of a real data and 5 options of the synthetic data of varying difficulty.
The real dataset consists of 25 people involved into the P4 alpha neurofeedback training. Its total size is about 16.3 hours. A more detailed instruction for this file is provided in the file Real dataset instructions.txt.
Synthetic data is generated in 5 different ways: sine wave with white noise, sine wave with pink noise, narrow-band filtered pink noise sample with pink noise, state-space model with white noise and state-space model with pink noise. Each of these datasets has about 34.5 hours of data. It is generated similarly to (Wodeyar et al, 2021). A more detailed instruction for the synthetic dataset can be found in the file Synthetic datasets instructions.txt.
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Additional details
References
- Anirudh Wodeyar, Mark Schatza, Alik S Widge, Uri T Eden, Mark A Kramer (2021) A state space modeling approach to real-time phase estimation eLife 10:e68803 https://doi.org/10.7554/eLife.68803