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Meta's open foundation model that predicts how the human brain responds to video, audio, and text — try the interactive demo, no signup.

About TRIBE v2

TRIBE v2 is Meta AI's open foundation model for predicting human brain activity in response to naturalistic stimuli (video, audio, text). It pairs V-JEPA2 (video), Wav2Vec-BERT (audio), and LLaMA 3.2 (text) encoders, was trained on 1,000+ hours of fMRI from 720 subjects, and delivers a ~70× resolution improvement and 2–3× accuracy gain over previous methods — including zero-shot prediction for individuals it has never seen. Meta released model weights, codebase, paper, and this interactive demo so researchers can run in-silico neuroscience experiments without scanner time.

CC BY-NC licensed.

Pricing model: Free

Features

  • Predicts fMRI brain responses to video, audio, and text
  • Tri-modal foundation model (V-JEPA2 + Wav2Vec-BERT + LLaMA 3.2)
  • Trained on 1,000+ hours of fMRI from 720 subjects
  • 70× resolution + 2–3× accuracy over prior methods
  • Interactive in-browser demo — upload a clip, see predictions
  • Model weights, code, and paper released (CC BY-NC)

FAQs

Common questions about TRIBE v2

What does TRIBE v2 do?
Given a clip of video, audio, or text, TRIBE v2 predicts the fMRI brain response it would trigger — at high spatial and temporal resolution.
Is it free?
Yes — the demo is free in the browser. Weights, code, and the paper are released under CC BY-NC for research use.
Who is it for?
Neuroscience researchers, cognitive scientists, and AI/ML researchers studying perception, attention, and brain–stimulus mapping.