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nm000129 NEMAR-native dataset

Liu2020 – BETA SSVEP benchmark dataset

The BETA SSVEP benchmark dataset comprises 64-channel EEG recordings from 70 healthy subjects performing a 40-target cued-spelling brain-computer interface task using steady-state visual evoked potentials (SSVEP). Recorded in a naturalistic classroom environment with joint frequency and phase modulation stimuli, this dataset provides a realistic benchmark for SSVEP-BCI applications with frequencies ranging from 8.0 to 15.8 Hz (0.2 Hz step) and sampling at 250 Hz.

EEG
Download zip Issues GitHub

Compute on this dataset

Two routes today, with a third (in-browser one-click submission) landing soon.

  1. NeuroScience Gateway (NSG) portal.

    NSG runs EEGLAB / Brainstorm / MNE pipelines on supercomputing time donated by SDSC. Create an account, point a job at this dataset's S3 prefix (s3://nemar/nm000129), and submit.
    nsgportal.org →

  2. Local processing with nemar-cli.

    Pull the dataset to your machine and run any toolbox locally. Honors the published version pinning. 

    npm install -g nemar-cli
nemar dataset clone nm000129
cd nm000129 && nemar dataset get
  3. Just the files.

    rclone, aria2c, or any HTTPS client works against data.nemar.org/nm000129/ — the manifest carries presigned S3 URLs.

Direct compute access is coming soon. One-click NSG submission from this page is scoped for a follow-up phase. Tracked on nemarOrg/website#6.
DOI 10.82901/nemar.nm000129

![DOI](https://doi.org/10.82901/nemar.nm000129)

BETA SSVEP benchmark dataset

BETA SSVEP benchmark dataset.

Dataset Overview

  • Code: Liu2020BETA
  • Paradigm: ssvep
  • DOI: 10.3389/fnins.2020.00627
  • Subjects: 70
  • Sessions per subject: 1
  • Events: 8.6=1, 8.8=2, 9=3, 9.2=4, 9.4=5, 9.6=6, 9.8=7, 10=8, 10.2=9, 10.4=10, 10.6=11, 10.8=12, 11=13, 11.2=14, 11.4=15, 11.6=16, 11.8=17, 12=18, 12.2=19, 12.4=20, 12.6=21, 12.8=22, 13=23, 13.2=24, 13.4=25, 13.6=26, 13.8=27, 14=28, 14.2=29, 14.4=30, 14.6=31, 14.8=32, 15=33, 15.2=34, 15.4=35, 15.6=36, 15.8=37, 8=38, 8.2=39, 8.4=40
  • Trial interval: [0, 3.0] s
  • File format: MAT

Acquisition

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

Participants

  • Number of subjects: 70
  • Health status: healthy
  • Age: mean=25.14, std=7.97, min=9, max=64
  • Gender distribution: male=42, female=28
  • BCI experience: mixed

Experimental Protocol

  • Paradigm: ssvep
  • Task type: cued-spelling
  • Number of classes: 40
  • Class labels: 8.6, 8.8, 9, 9.2, 9.4, 9.6, 9.8, 10, 10.2, 10.4, 10.6, 10.8, 11, 11.2, 11.4, 11.6, 11.8, 12, 12.2, 12.4, 12.6, 12.8, 13, 13.2, 13.4, 13.6, 13.8, 14, 14.2, 14.4, 14.6, 14.8, 15, 15.2, 15.4, 15.6, 15.8, 8, 8.2, 8.4
  • Trial duration: 3.0 s
  • Feedback type: visual
  • Stimulus type: JFPM visual flicker
  • Stimulus modalities: visual
  • Primary modality: visual
  • Synchronicity: synchronous
  • Mode: offline
  • Training/test split: False

HED Event Annotations

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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, 12.600000000000001, 12.8, 13.0, 13.2, 13.4, 13.600000000000001, 13.8, 14.0, 14.2, 14.4, 14.600000000000001, 14.8, 15.0, 15.2, 15.4, 15.600000000000001, 15.8] Hz
  • Frequency resolution: 0.2 Hz

Data Structure

  • Trials: 160
  • Blocks per session: 4

Preprocessing

  • Data state: epoched
  • Notch filter: 50 Hz
  • Filter type: zero-phase FIR
  • Downsampled to: 250.0 Hz

Signal Processing

  • Classifiers: TRCA, msTRCA, FBCCA, CCA
  • Feature extraction: CCA, TRCA, FBCCA
  • Frequency bands: bandpass=[3.0, 100.0] Hz
  • Spatial filters: CCA, TRCA

Cross-Validation

  • Method: leave-one-block-out
  • Folds: 4
  • Evaluation type: within_subject

BCI Application

  • Applications: speller
  • Environment: classroom
  • Online feedback: True

Tags

  • Pathology: healthy
  • Modality: visual
  • Type: perception

Documentation

  • DOI: 10.3389/fnins.2020.00627
  • License: Non-commercial research use
  • Investigators: Bingchuan Liu, Xiaoshan Huang, Yijun Wang, Xiaogang Chen, Xiaorong Gao
  • Senior author: Xiaorong Gao
  • Institution: Tsinghua University
  • Department: Department of Biomedical Engineering, Tsinghua University
  • Country: CN
  • Repository: Tsinghua BCI Lab
  • Data URL: http://bci.med.tsinghua.edu.cn/upload/liubingchuan/
  • Publication year: 2020
  • Funding: National Key Research and Development Program of China (No. 2017YFB1002505); Strategic Priority Research Program of Chinese Academy of Sciences (No. XDB32040200); Key Research and Development Program of Guangdong Province (No. 2018B030339001); National Natural Science Foundation of China (Grant No. 61431007)
  • Ethics approval: Ethics Committee of Tsinghua University, No. 20190002
  • Keywords: SSVEP, BCI, EEG, benchmark, JFPM

References

B. Liu, X. Huang, Y. Wang, X. Chen, and X. Gao, "BETA: A Large Benchmark Database Toward SSVEP-BCI Application," Frontiers in Neuroscience, vol. 14, p. 627, 2020. DOI: 10.3389/fnins.2020.00627 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

Generated by MOABB 1.4.3 (Mother of All BCI Benchmarks) https://github.com/NeuroTechX/moabb

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