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EEG Insights

Unraveling how the brain visualizes seen and imagined images through EEG

Overview

EEG-based study comparing visual perception and imagery.

Topographic map showing 32-channel EEG electrode placement on the scalp.
Topographic map showing 32-channel EEG electrode placement on the scalp.
Biostatistics Role

The biostatistics team validates findings by analyzing EEG stationarity, covariance, spectral power, and connectivity, using rigorous permutation testing and corrections to ensure robust, interpretable results guiding feature selection.

Network diagram illustrating EEG channel connectivity and coherence patterns during visual tasks.
Network diagram illustrating EEG channel connectivity and coherence patterns during visual tasks.
AI Pipeline

Our AI system uses graph neural networks and temporal transformers to decode EEG signals, aligning neural, image, and text data into a shared space for image reconstruction from imagined content.

Gallery

EEG topography map showing 32-channel electrode layout during visual perception task.
EEG topography map showing 32-channel electrode layout during visual perception task.
Coherence network graph illustrating functional connectivity differences between perception and imagery.
Coherence network graph illustrating functional connectivity differences between perception and imagery.
Frequency-band power plot comparing alpha and beta rhythms across visual conditions.
Frequency-band power plot comparing alpha and beta rhythms across visual conditions.
Diagram contrasting brain activity patterns during viewing versus imagining an animal image.
Diagram contrasting brain activity patterns during viewing versus imagining an animal image.
Illustration of the AI pipeline from EEG signal input to image reconstruction output.
Illustration of the AI pipeline from EEG signal input to image reconstruction output.
Graph neural network visualization highlighting electrode nodes and adaptive edges.
Graph neural network visualization highlighting electrode nodes and adaptive edges.

Visualizing neural patterns and AI reconstruction steps

BIBLIOGRAPHY

Research References

A comprehensive list of foundational datasets, peer-reviewed literature, and methodology frameworks supporting our neural pattern visualization and EEG imagery analysis.

[5] Maris & Oostenveld (2007)

[6] Vaswani et al. (2017)

[7] Rombach et al. (2022)

[1] Gao et al. (2026), VI-EEG dataset: https://doi.org/10.1038/s41597-025-06512-5

[2] Guttmann-Flury et al. (2025): https://doi.org/10.1038/s41597-025-04861-9

[3] Xie et al. (2020), posterior alpha: https://doi.org/10.1016/j.cub.2020.04.074

[4] Ombao & Pinto (2024): https://doi.org/10.1016/j.ecosta.2022.10.005

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