SSVEP Wang 2016 dataset

SSVEP Wang 2016 dataset.

Dataset Overview

• Code: Wang2016
• Paradigm: ssvep
• DOI: 10.1109/TNSRE.2016.2627556
• Subjects: 34
• Sessions per subject: 1
• Events: 8=1, 9=2, 10=3, 11=4, 12=5, 13=6, 14=7, 15=8, 8.2=9, 9.2=10, 10.2=11, 11.2=12, 12.2=13, 13.2=14, 14.2=15, 15.2=16, 8.4=17, 9.4=18, 10.4=19, 11.4=20, 12.4=21, 13.4=22, 14.4=23, 15.4=24, 8.6=25, 9.6=26, 10.6=27, 11.6=28, 12.6=29, 13.6=30, 14.6=31, 15.6=32, 8.8=33, 9.8=34, 10.8=35, 11.8=36, 12.8=37, 13.8=38, 14.8=39, 15.8=40
• Trial interval: [0.5, 5.5] s
• File format: MATLAB MAT
• Data preprocessed: True

Acquisition

• Sampling rate: 250.0 Hz
• Number of channels: 64
• Channel types: eeg=64
• Channel names: AF3, AF4, C1, C2, C3, C4, C5, C6, CB1, CB2, CP1, CP2, CP3, CP4, CP5, CP6, CPz, Cz, F1, F2, F3, F4, F5, F6, F7, F8, FC1, FC2, FC3, FC4, FC5, FC6, FCz, FT7, FT8, Fp1, Fp2, Fpz, Fz, M1, M2, O1, O2, Oz, P1, P2, P3, P4, P5, P6, P7, P8, PO3, PO4, PO5, PO6, PO7, PO8, POz, Pz, T7, T8, TP7, TP8
• Montage: standard_1005
• Hardware: Synamps2 EEG system (Neuroscan, Inc.)
• Reference: Cz
• Line frequency: 50.0 Hz
• Online filters: {'bandpass': [0.15, 200], 'notch': 50}
• Impedance threshold: 10 kOhm

Participants

• Number of subjects: 34
• Health status: healthy
• Age: mean=22.0, min=17, max=34
• Gender distribution: female=17, male=18
• BCI experience: 8 experienced, 27 naïve
• Species: human

Experimental Protocol

• Paradigm: ssvep
• Number of classes: 40
• Class labels: 8, 9, 10, 11, 12, 13, 14, 15, 8.2, 9.2, 10.2, 11.2, 12.2, 13.2, 14.2, 15.2, 8.4, 9.4, 10.4, 11.4, 12.4, 13.4, 14.4, 15.4, 8.6, 9.6, 10.6, 11.6, 12.6, 13.6, 14.6, 15.6, 8.8, 9.8, 10.8, 11.8, 12.8, 13.8, 14.8, 15.8
• Trial duration: 6.0 s
• Study design: Cue-guided target selecting task using a 40-target BCI speller with joint frequency and phase modulation (JFPM) approach
• Stimulus type: visual flicker
• Stimulus modalities: visual
• Primary modality: visual
• Synchronicity: synchronous
• Mode: offline
• Instructions: Subjects were asked to shift their gaze to the target as soon as possible after cue and avoid eye blinks during the 5-s stimulation duration
• Stimulus presentation: SoftwareName=MATLAB Psychophysics Toolbox Ver. 3 (PTB-3), display=23.6-in LCD monitor (Acer GD245 HQ, response time: 2 ms), resolution=1920 × 1080 pixels at 60 Hz, viewingdistance=70 cm, stimulussize=140 × 140 pixels (3.2° × 3.2°), charactersize=32 × 32 pixels (0.7° × 0.7°), matrixsize=1510 × 1037 pixels (34° × 24°), matrixlayout=5 × 8 stimulus matrix, interstimulus_distance=50 pixels vertical and horizontal, method=sampled sinusoidal stimulation

HED Event Annotations

Schema: HED 8.4.0 | Browse: https://www.hedtags.org/hed-schema-browser

  8
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/8

  9
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/9

  10
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/10

  11
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/11

  12
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/12

  13
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/13

  14
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/14

  15
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/15

  8.2
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/8_2

  9.2
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/9_2

  10.2
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/10_2

  11.2
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/11_2

  12.2
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/12_2

  13.2
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/13_2

  14.2
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/14_2

  15.2
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/15_2

  8.4
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/8_4

  9.4
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/9_4

  10.4
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/10_4

  11.4
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/11_4

  12.4
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/12_4

  13.4
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/13_4

  14.4
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/14_4

  15.4
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/15_4

  8.6
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/8_6

  9.6
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/9_6

  10.6
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/10_6

  11.6
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/11_6

  12.6
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/12_6

  13.6
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/13_6

  14.6
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/14_6

  15.6
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/15_6

  8.8
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/8_8

  9.8
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/9_8

  10.8
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/10_8

  11.8
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/11_8

  12.8
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/12_8

  13.8
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/13_8

  14.8
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/14_8

  15.8
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/15_8

Paradigm-Specific Parameters

• Detected paradigm: ssvep
• Stimulus frequencies: [8.0, 8.2, 8.4, 8.6, 8.8, 9.0, 9.2, 9.4, 9.6, 9.8, 10.0, 10.2, 10.4, 10.6, 10.8, 11.0, 11.2, 11.4, 11.6, 11.8, 12.0, 12.2, 12.4, 12.6, 12.8, 13.0, 13.2, 13.4, 13.6, 13.8, 14.0, 14.2, 14.4, 14.6, 14.8, 15.0, 15.2, 15.4, 15.6, 15.8] Hz
• Frequency resolution: 0.2 Hz
• Number of targets: 40
• Number of repetitions: 6
• Cue duration: 0.5 s

Data Structure

• Trials: 240
• Trials per class: per_target=6
• Blocks per session: 6
• Trials context: 40 trials per block corresponding to all 40 characters in random order

Preprocessing

• Data state: Raw epochs extracted from continuous EEG recordings according to stimulus onsets, downsampled to 250 Hz, no digital filters applied
• Preprocessing applied: True
• Steps: Epoch extraction according to stimulus onsets from event channel, Downsampling from 1000 Hz to 250 Hz, No digital filters applied in preprocessing
• Downsampled to: 250.0 Hz
• Epoch window: [-0.5, 5.5]
• 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.

Signal Processing

• Classifiers: CCA, FBCCA
• Feature extraction: Canonical Correlation Analysis, Filter Bank CCA
• Frequency bands: analyzed=[7.0, 90.0] Hz

Cross-Validation

• Method: leave-one-out (on six blocks)
• Folds: 6
• Evaluation type: within_subject

Performance (Original Study)

• Itr: 117.75 bits/min
• Peak Itr Fbcca 0.55S Gaze: 117.75
• Peak Itr Fbcca 2S Gaze: 68.99
• Peak Itr Cca 0.55S Gaze: 89.89
• Peak Itr Cca 2S Gaze: 56.03
• Visual Latency Ms: 136.91
• Visual Latency Std Ms: 18.4

BCI Application

• Applications: speller
• Environment: dimly lit soundproof room
• Online feedback: False

Tags

• Pathology: Healthy
• Modality: Visual
• Type: Perception

Documentation

• Description: A benchmark SSVEP dataset acquired with a 40-target BCI speller using joint frequency and phase modulation (JFPM) approach
• DOI: 10.1109/TNSRE.2016.2627556
• License: CC-BY-4.0
• Investigators: Yijun Wang, Xiaogang Chen, Xiaorong Gao, Shangkai Gao
• Senior author: Shangkai Gao
• Contact: wangyj@semi.ac.cn; chenxg@bme.cams.cn; gxrdea@tsinghua.edu.cn; gsk-dea@tsinghua.edu.cn
• Institution: Tsinghua University
• Department: Department of Biomedical Engineering, Tsinghua University
• Address: Beijing, China
• Country: CN
• Repository: BNCI Horizon 2020
• Data URL: http://bci.med.tsinghua.edu.cn/download.html
• Publication year: 2016
• 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)
• Ethics approval: Research Ethics Committee of Tsinghua University
• Keywords: Brain–computer interface (BCI), electroencephalogram (EEG), joint frequency and phase modulation (JFPM), public data set, steady-state visual evoked potential (SSVEP)

External Links

• Source: http://bci.med.tsinghua.edu.cn/download.html
• Bnci Horizon: https://bnci-horizon-2020.eu/database/data-sets

Abstract

This paper presents a benchmark steady-state visual evoked potential (SSVEP) dataset acquired with a 40-target brain–computer interface (BCI) speller. The dataset consists of 64-channel Electroencephalogram (EEG) data from 35 healthy subjects (8 experienced and 27 naïve) while they performed a cue-guided target selecting task. The virtual keyboard of the speller was composed of 40 visual flickers, which were coded using a joint frequency and phase modulation (JFPM) approach. The stimulation frequencies ranged from 8 Hz to 15.8 Hz with an interval of 0.2 Hz. The phase difference between two adjacent frequencies was 0.5π. For each subject, the data included six blocks of 40 trials corresponding to all 40 flickers indicated by a visual cue in a random order. The stimulation duration in each trial was five seconds.

Methodology

The study used a cue-guided target selecting task with a 40-target BCI speller. Stimuli were presented on a 23.6-in LCD monitor at 60 Hz using sampled sinusoidal stimulation method. Each trial started with a 0.5-s target cue, followed by 5 s of concurrent flickering of all stimuli, and ended with 0.5 s blank screen. The experiment included six blocks per subject, with 40 trials per block in random order. EEG data were recorded using Synamps2 system at 1000 Hz with 64 electrodes, referenced to Cz. Data were preprocessed by extracting epochs according to stimulus onsets and downsampling to 250 Hz. The JFPM approach encoded 40 characters using frequencies from 8-15.8 Hz (0.2 Hz interval) and phases from 0 to 19.5π (0.5π interval). Performance was evaluated using CCA and FBCCA methods with leave-one-out cross-validation.

References

Wang, Y., Chen, X., Gao, X., & Gao, S. (2016). A benchmark dataset for SSVEP-based brain–computer interfaces. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 25(10), 1746-1752. doi: 10.1109/TNSRE.2016.2627556. Appelhoff, S., Sanderson, M., Brooks, T., Vliet, M., Quentin, R., Holdgraf, C., Chaumon, M., Mikulan, E., Tavabi, K., Hochenberger, R., Welke, D., Brunner, C., Rockhill, A., Larson, E., Gramfort, A. and Jas, M. (2019). MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis. Journal of Open Source Software 4: (1896). https://doi.org/10.21105/joss.01896

Pernet, C. R., Appelhoff, S., Gorgolewski, K. J., Flandin, G., Phillips, C., Delorme, A., Oostenveld, R. (2019). EEG-BIDS, an extension to the brain imaging data structure for electroencephalography. Scientific Data, 6, 103. https://doi.org/10.1038/s41597-019-0104-8

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