A foundation model of vision, audition, and language for in-silico neuroscience

• URL: http://arxiv.org/abs/2605.04326v1
• Date: Tue, 05 May 2026 22:13:48 GMT
• Title: A foundation model of vision, audition, and language for in-silico neuroscience
• Abstract summary: We introduce TRIBE v2, a tri-modal foundation model capable of predicting human brain activity in a variety of naturalistic and experimental conditions.<n>We demonstrate that our model accurately predicts high-resolution brain responses for novel stimuli, tasks and subjects, delivering several-fold improvements in accuracy.
• Score: 6.879219950889638
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Cognitive neuroscience is fragmented into specialized models, each tailored to specific experimental paradigms, hence preventing a unified model of cognition in the human brain. Here, we introduce TRIBE v2, a tri-modal (video, audio and language) foundation model capable of predicting human brain activity in a variety of naturalistic and experimental conditions. Leveraging a unified dataset of over 1,000 hours of fMRI across 720 subjects, we demonstrate that our model accurately predicts high-resolution brain responses for novel stimuli, tasks and subjects, superseding traditional linear encoding models, delivering several-fold improvements in accuracy. Critically, TRIBE v2 enables in silico experimentation: tested on seminal visual and neuro-linguistic paradigms, it recovers a variety of results established by decades of empirical research. Finally, by extracting interpretable latent features, TRIBE v2 reveals the fine-grained topography of multisensory integration. These results establish artificial intelligence as a unifying framework for exploring the functional organization of the human brain.

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