Meta's open foundation model that predicts how the human brain responds to video, audio, and text — try the interactive demo, no signup.
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.
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.
Tags: AI, Neuroscience, Research, Open Source, Meta AI, Foundation Model
Try TRIBE v2Given a clip of video, audio, or text, TRIBE v2 predicts the fMRI brain response it would trigger — at high spatial and temporal resolution.
Yes — the demo is free in the browser. Weights, code, and the paper are released under CC BY-NC for research use.
Neuroscience researchers, cognitive scientists, and AI/ML researchers studying perception, attention, and brain–stimulus mapping.