{
  "Name": "Wang2016 – SSVEP Wang 2016 dataset",
  "BIDSVersion": "1.9.0",
  "HEDVersion": "8.4.0",
  "DatasetType": "derivative",
  "License": "CC-BY-4.0",
  "Authors": [
    "Yijun Wang",
    "Xiaogang Chen",
    "Xiaorong Gao",
    "Shangkai Gao"
  ],
  "Funding": [
    "National Natural Science Foundation of China (No. 61431007, No. 91220301, and No. 91320202)",
    "National High-tech R&D Program (863) of China (No. 2012AA011601)",
    "Recruitment Program for Young Professionals",
    "Young Talents Lift Project of Chinese Association of Science and Technology",
    "PUMC Youth Fund (No. 3332016101)"
  ],
  "EthicsApprovals": [
    "Research Ethics Committee of Tsinghua University"
  ],
  "ReferencesAndLinks": [
    "http://bci.med.tsinghua.edu.cn/download.html"
  ],
  "GeneratedBy": [
    {
      "CodeURL": "https://github.com/NeuroTechX/moabb",
      "Name": "moabb",
      "Description": "Mother of All BCI Benchmarks",
      "Version": "1.4.3"
    }
  ],
  "SourceDatasets": [
    {
      "DOI": "10.1109/TNSRE.2016.2627556",
      "URL": "http://bci.med.tsinghua.edu.cn/download.html"
    }
  ],
  "Keywords": [
    "Brain–computer interface (BCI)",
    "electroencephalogram (EEG)",
    "joint frequency and phase modulation (JFPM)",
    "public data set",
    "steady-state visual evoked potential (SSVEP)"
  ],
  "PublicationYear": 2016,
  "ExperimentName": "Wang2016",
  "Description": "SSVEP Wang 2016 dataset.\n\n\nDataset summary:\n\n#Subj     34\n#Chan     64\n#Classes     40\n#Trials / class      6\nTrials length    5 s\nFreq 250 Hz\n#Sessions      1\n\n\nParticipants:\n\n- Population: healthy\n- Age: 22 (range: 17-34) years\n- BCI experience: 8 experienced, 27 naïve\n\n\nEquipment:\n\n- Amplifier: Synamps2 EEG system (Neuroscan, Inc.)\n- Montage: standard_1005\n- Reference: Cz\n\n\nPreprocessing:\n\n- Data state: Raw epochs extracted from continuous EEG recordings according to stimulus onsets, downsampled to 250 Hz, no digital filters applied\n- Steps: Epoch extraction according to stimulus onsets from event channel, Downsampling from 1000 Hz to 250 Hz, No digital filters applied in preprocessing\n- Notes: Data epochs include 0.5 s before stimulus onset, 5 s for stimulation, and 0.5 s after stimulus offset. Upper bound frequency of SSVEP harmonics is around 90 Hz.\n\n\nData Access:\n\n- DOI: 10.1109/TNSRE.2016.2627556\n- Data URL: http://bci.med.tsinghua.edu.cn/download.html\n- Repository: BNCI Horizon 2020\n\n\nExperimental Protocol:\n\n- Paradigm: ssvep\n- Stimulus: visual flicker\n\nDataset from [1]_.\n\nThis dataset gathered SSVEP-BCI recordings of 35 healthy subjects (17\nfemales, aged 17-34 years, mean age: 22 years) focusing on 40 characters\nflickering at different frequencies (8-15.8 Hz with an interval of 0.2 Hz).\nFor each subject, the experiment consisted of 6 blocks. Each block\ncontained 40 trials corresponding to all 40 characters indicated in a\nrandom order. Each trial started with a visual cue (a red square)\nindicating a target stimulus. The cue appeared for 0.5 s on the screen.\nSubjects were asked to shift their gaze to the target as soon as possible\nwithin the cue duration. Following the cue offset, all stimuli started to\nflicker on the screen concurrently and lasted 5 s. After stimulus offset,\nthe screen was blank for 0.5 s before the next trial began, which allowed\nthe subjects to have short breaks between consecutive trials. Each trial\nlasted a total of 6 s. To facilitate visual fixation, a red triangle\nappeared below the flickering target during the stimulation period. In each\nblock, subjects were asked to avoid eye blinks during the stimulation\nperiod. To avoid visual fatigue, there was a rest for several minutes\nbetween two consecutive blocks.\n\nEEG data were acquired using a Synamps2 system (Neuroscan, Inc.) with a\nsampling rate of 1000 Hz. The amplifier frequency passband ranged from\n0.15 Hz to 200 Hz. Sixty-four channels covered the whole scalp of the\nsubject and were aligned according to the international 10-20 system.\nThe ground was placed on midway between Fz and FPz. The reference was\nlocated on the vertex. Electrode impedances were kept below 10 KΩ. To\nremove the common power-line noise, a notch filter at 50 Hz was applied\nin data recording. Event triggers generated by the computer to the\namplifier and recorded on an event channel synchronized to the EEG data.\n\nThe continuous EEG data was segmented into 6 s epochs (500 ms pre-stimulus,\n5.5 s post-stimulus onset). The epochs were subsequently downsampled to\n250 Hz. Thus each trial consisted of 1500 time points. Finally, these data\nwere stored as double-precision floating-point values in MATLAB and were\nnamed as subject indices (i.e., S01.mat, …, S35.mat). For each file, the\ndata loaded in MATLAB generate a 4-D matrix named ‘data’ with dimensions\nof [64, 1500, 40, 6]. The four dimensions indicate ‘Electrode index’,\n‘Time points’, ‘Target index’, and ‘Block index’. The electrode positions\nwere saved in a ‘64-channels.loc’ file. Six trials were available for each\nSSVEP frequency. Frequency and phase values for the 40 target indices were\nsaved in a ‘Freq_Phase.mat’ file.\n\nInformation for all subjects was listed in a ‘Sub_info.txt’ file. For each\nsubject, there are five factors including ‘Subject Index’, ‘Gender’, ‘Age’,\n'Handedness', and 'Group'. Subjects were divided into an 'experienced'\ngroup (eight subjects, S01-S08) and a 'naive' group (27 subjects, S09-S35)\naccording to their experience in SSVEP-based BCIs.\n\nWarnings\n--------\nThe original dataset includes two channels labeled 'CB1' and 'CB2',\nwhich are not part of the standard 10-20 EEG montage.\nAlthough the authors of Wang2016 state that the 10-20 layout was used,\nthe provided channel location file suggests that 'CB1' and 'CB2'\nmay correspond approximately to 'P9' and 'P10'. However, this mapping is\nnot confirmed, and the exact locations remain uncertain.\n\nIn this implementation, we treat 'CB1' and 'CB2' as standard EEG channels,\nfollowing the approach used by the authors.\n\nUsers should be aware of this ambiguity when interpreting spatial analyses\nor when comparing to other datasets with strictly standard montages.\n\nReferences\n----------\n.. [1] Wang, Y., Chen, X., Gao, X., & Gao, S. (2016). A benchmark dataset for\nSSVEP-based brain–computer interfaces. IEEE Transactions on Neural\nSystems and Rehabilitation Engineering, 25(10), 1746-1752.\ndoi: 10.1109/TNSRE.2016.2627556.",
  "DatasetDOI": "10.82901/nemar.nm000126",
  "Version": "1.0.2"
}