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loganf26/
tribev2-subcortical

Name: tribev2-subcortical
Availability: InStock

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TRIBE v2 Subcortical Head (Lahner)

This model provides subcortical fMRI prediction weights for the TRIBE v2 architecture.
It predicts BOLD activity in subcortical brain regions (e.g. hippocampus, amygdala, pallidum) from multimodal inputs (video, audio, text).

Model Details

Developed by: Logan Fernandez
Model type: Multimodal fMRI encoding model (regression)
Base model: TRIBE v2
License: CC BY-NC 4.0

Uses

Predict deep brain activity from naturalistic stimuli
Study stimulus → brain response relationships
Analyze emotional response to stimuli
Make the brain watch reels (See Github repo)

Limitations

Subject-specific behavior for Lahner-style subjects, tuned to short-form media
Correlation, not causation

Training

Dataset: Lahner2024Bold (BOLD Moments)
Features: video (V-JEPA), audio (Wac2Vert), text (Qwen3B)
Projection: subcortical mask

Evaluation

Metric: Pearson correlation
Result: r = 0.165 (test split)

This reflects the difficulty of predicting subcortical activity, which is noisier and lower resolution than cortical signals.

Repository

https://github.com/Enzyme0/homunculus

Contact

Logan Fernandez loganfe@outlook.com

Acknowledgements

This model builds on TRIBE-V2 and is intended as a downstream or derived component built from that work.

Citation

Please cite both this model and TRIBE-V2 when relevant:

bibtex

@article{dAscoli2026TribeV2,
  title={A foundation model of vision, audition, and language for in-silico neuroscience},
  author={d'Ascoli, St{\'e}phane and Rapin, J{\'e}r{\'e}my and Benchetrit, Yohann and Brookes, Teon and Begany, Katelyn and Raugel, Jos{\'e}phine and Banville, Hubert and King, Jean-R{\'e}mi},
  year={2026}
}

loganf26/tribev2-subcortical