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EEG Insights

Unraveling how the brain visualizes seen and imagined images through EEG

A technical schematic of neural pathways glowing with silver light, transitioning into a pixelated, semi-reconstructed geometric shape on a dark slate background.
A technical schematic of neural pathways glowing with silver light, transitioning into a pixelated, semi-reconstructed geometric shape on a dark slate background.
Overview
Gallery
References
Neural Reconstruction

Decoding the Mind's Eye

By bridging the gap between subjective mental imagery and computational synthesis, our Brain-Computer Interface decodes complex EEG signals to reconstruct the vivid images formed purely within human imagination.

How BCI Reconstructs Imagination

Using high-density EEG arrays, we capture the subtle neural oscillations triggered during active visualization. Machine learning models then map these electrical patterns to latent feature spaces, generating high-fidelity visual outputs.

Poster Overview

Reconstructed Gallery

References

Examine the experimental design, comparative analysis, and statistical frameworks.

Browse the visual comparisons between perception and real-time mental imagery.

Review the peer-reviewed literature, datasets, and methodology supporting this study.

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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