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# Visual imagery EEG dataset from Gao et al 2026

Visual imagery EEG dataset from Gao et al 2026.

## Dataset Overview

- **Code**: Gao2026
- **Paradigm**: imagery
- **DOI**: 10.1038/s41597-025-06512-5
- **Subjects**: 22
- **Sessions per subject**: 2
- **Events**: dog=1, bird=2, fish=3, pentagram=11, square=12, circle=13, scissor=21, watch=22, cup=23, chair=24
- **Trial interval**: [0, 4] s
- **Runs per session**: 3
- **File format**: BDF

## Acquisition

- **Sampling rate**: 1000.0 Hz
- **Number of channels**: 32
- **Channel types**: eeg=32
- **Montage**: standard_1005
- **Hardware**: Neuracle NeuSenW32
- **Reference**: CPz
- **Ground**: AFz
- **Sensor type**: Ag/AgCl
- **Line frequency**: 50.0 Hz
- **Online filters**: {'sampling_rate': 1000}

## Participants

- **Number of subjects**: 22
- **Health status**: healthy
- **Age**: min=20.0, max=23.0
- **Gender distribution**: male=17, female=5
- **Species**: human

## Experimental Protocol

- **Paradigm**: imagery
- **Number of classes**: 10
- **Class labels**: dog, bird, fish, pentagram, square, circle, scissor, watch, cup, chair
- **Trial duration**: 4.0 s
- **Study design**: Visual imagery of animals, figures, and objects with simultaneous 32-channel EEG recording
- **Feedback type**: none
- **Stimulus type**: image cues
- **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

```
  dog
    ├─ Sensory-event
    └─ Label/dog

  bird
    ├─ Sensory-event
    └─ Label/bird

  fish
    ├─ Sensory-event
    └─ Label/fish

  pentagram
    ├─ Sensory-event
    └─ Label/pentagram

  square
    ├─ Sensory-event
    └─ Label/square

  circle
    ├─ Sensory-event
    └─ Label/circle

  scissor
    ├─ Sensory-event
    └─ Label/scissor

  watch
    ├─ Sensory-event
    └─ Label/watch

  cup
    ├─ Sensory-event
    └─ Label/cup

  chair
    ├─ Sensory-event
    └─ Label/chair

```
## Paradigm-Specific Parameters

- **Detected paradigm**: motor_imagery
- **Imagery tasks**: dog, bird, fish, pentagram, square, circle, scissor, watch, cup, chair

## Data Structure

- **Trials**: 16800
- **Trials context**: 20 subjects x 2 sessions x 400 trials + 2 subjects x 1 session x 400 trials = 16800

## Signal Processing

- **Classifiers**: EEGNet, CSP+KNN
- **Feature extraction**: CSP, deep_learning
- **Frequency bands**: bandpass=[5.0, 30.0] Hz
- **Spatial filters**: CSP, CAR

## Cross-Validation

- **Method**: train-test split
- **Evaluation type**: within_subject

## BCI Application

- **Applications**: human_machine_interaction
- **Environment**: laboratory
- **Online feedback**: False

## Tags

- **Pathology**: Healthy
- **Modality**: Visual
- **Type**: Research

## Documentation

- **DOI**: 10.1038/s41597-025-06512-5
- **License**: CC-BY-NC-ND-4.0
- **Investigators**: Jing'ao Gao, Yao Liu, Zhengshuang Li, Kaixin Huang, Fan Wang, Jiaping Xu, Lei Zhao, Tianwen Li, Yunfa Fu
- **Institution**: Kunming University of Science and Technology
- **Country**: CN
- **Repository**: Figshare
- **Data URL**: https://doi.org/10.6084/m9.figshare.30227503.v1
- **Publication year**: 2026

## References

Gao, J., Liu, Y., Li, Z., Huang, K., Wang, F., Xu, J., Zhao, L., Li, T., & Fu, Y. (2026). An EEG Dataset for Visual Imagery-Based Brain-Computer Interface. Scientific Data. https://doi.org/10.1038/s41597-025-06512-5

Gao, J. et al. (2026). EEG Dataset for Visual Imagery. Figshare. https://doi.org/10.6084/m9.figshare.30227503.v1
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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