The zip archive contains EEG data from a newly developed brain-computer interface paradigm. The method is described in [1], and the dataset has been recorded for the application described in [2]. The two folders in the archive contain data from the training (offline) session and from the online session. Training data: Each subject has two training sessions. The .xdf files were generated by the Lab Streaming Layer (https://github.com/sccn/labstreaminglayer) from EEG data that were recorded using a BioSemi 32 channel amplifier. The files name after (subject_number)_(session_num).xdf. Each file includes 200 trials (50 trials for each direction). Online data: Each file contains data from one round of the game. The file name pattern is (subject_num)_(repeat_num) _(ramdon_background_num).mat. The Matlab data structure contains the following fields: data. fsample: sampling rate (512 Hz) data.trial: EEG signals for each step data.time: time series of EEG signals for each step data.class: classifier output for each step [1] Maye A, Zhang D, Engel AK (2017) "Utilizing Retinotopic Mapping for a Multi-Target SSVEP BCI With a Single Flicker Frequency", IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 25, no. 7, pp. 1026-1036, July 2017, doi: 10.1109/TNSRE.2017.2666479. [2] Chen J, Zhang D, Engel AK, Gong Q, Maye A (2017) "Application of a single-flicker online SSVEP BCI" for spatial navigation", PLoS ONE, 12(5): e0178385. https://doi.org/10.1371/journal.pone.0178385

{"references": ["Maye A, Zhang D, Engel AK (2017) \"Utilizing Retinotopic Mapping for a Multi-Target SSVEP BCI With a Single Flicker Frequency\", IEEE Transactions on Neural Systems and Rehabilitation Engineering, in press.", "Chen J, Zhang D, Engel AK, Gong Q, Maye A (2017) \"Application of a single-flicker online SSVEP BCI for spatial navigation\", PLoS ONE, in press."]}

Funding: Deutsche Forschungsgemeinschaft (www.dfg.de) TRR169/B1/Z2, AKE Landesforschungsförderung Hamburg - CROSS FV25, AKE National Key Research and Development Plan (www.most.gov.cn) Grant No. 2016YFB1001200, DZ Tsinghua Fudaoyuan Research Fund (tsinghua.edu.cn), JC