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nm000131 NEMAR-native dataset

Wang2021 – Combined SSVEP dataset with single stimulus location for two inputs

A derivative EEG dataset implementing a combined steady-state visual evoked potential (SSVEP) brain-computer interface paradigm with spatially overlapping stimuli presented at a single location. The dataset comprises 8 healthy subjects performing a covert attention task to discriminate four arrow directions (up, down, left, right) flickering at distinct frequencies (7.73–14.17 Hz) derived from an 85 Hz CRT refresh rate. EEG signals were recorded at 1000 Hz using a 32-channel ANT Neuro system across two experimental schemes examining different attentional mechanisms.

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/nm000131), 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 nm000131
cd nm000131 && nemar dataset get
  3. Just the files.

    rclone, aria2c, or any HTTPS client works against data.nemar.org/nm000131/ — 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.nm000131

![DOI](https://doi.org/10.82901/nemar.nm000131)

Combined SSVEP dataset with single stimulus location for two inputs

Combined SSVEP dataset with single stimulus location for two inputs.

Dataset Overview

  • Code: Wang2021Combined
  • Paradigm: ssvep
  • DOI: 10.1111/ejn.15030
  • Subjects: 8
  • Sessions per subject: 1
  • Events: 14.17=1, 12.14=2, 9.44=3, 7.73=4
  • Trial interval: [0.0, 5.0] s
  • File format: CNT

Acquisition

  • Sampling rate: 1000.0 Hz
  • Number of channels: 31
  • Channel types: eeg=31, eog=2
  • Montage: standard_1005
  • Hardware: eego mylab (ANT Neuro)
  • Line frequency: 50.0 Hz

Participants

  • Number of subjects: 8
  • Health status: healthy

Experimental Protocol

  • Paradigm: ssvep
  • Task type: covert_attention
  • Number of classes: 4
  • Class labels: 14.17, 12.14, 9.44, 7.73
  • Trial duration: 5.0 s
  • Study design: One-to-two combined SSVEP with overlapping stimuli
  • Feedback type: none
  • Stimulus type: overlapping SSVEP arrows (CRT 85 Hz)
  • Stimulus modalities: visual
  • Primary modality: visual
  • Synchronicity: synchronous
  • Mode: offline

HED Event Annotations

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

  14.17
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/14_17

  12.14
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/12_14

  9.44
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/9_44

  7.73
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Label/7_73

Paradigm-Specific Parameters

  • Detected paradigm: ssvep
  • Stimulus frequencies: [14.17, 12.14, 9.44, 7.73] Hz

Data Structure

  • Blocks per session: 2

BCI Application

  • Environment: lab

Tags

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

Documentation

  • DOI: 10.1111/ejn.15030
  • License: CC BY 4.0
  • Investigators: Lu Wang, Zhenhao Zhang, Dan Han, Zhijun Zhang, Zhifang Liu, Wei Liu
  • Senior author: Zhijun Zhang
  • Institution: Shandong University
  • Country: CN
  • Repository: Zenodo
  • Data URL: https://zenodo.org/records/18873228
  • Publication year: 2021

References

L. Wang, Z. Zhang, D. Han, Z. Zhang, Z. Liu, and W. Liu, "Single stimulus location for two inputs: A combined brain-computer interface based on Steady-State Visual Evoked Potential (SSVEP)," European Journal of Neuroscience, vol. 53, no. 3, pp. 861-875, 2021. DOI: 10.1111/ejn.15030 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

Files

14 top-level entries · 2.57 GB total