OmniMouse: Scaling properties of multi-modal, multi-task Brain Models on 150B Neural Tokens
Researchers have developed OmniMouse, a multi-modal, multi-task model trained on over 150 billion neural tokens from a mouse's visual cortex. This model demonstrates state-of-the-art performance in neural prediction, behavioral decoding, and neural forecasting, outperforming specialized baselines. Unlike typical AI scaling trends where model size is the primary driver, OmniMouse's performance scales reliably with data, but gains from increasing model size saturate, suggesting brain modeling remains data-limited. AI
IMPACT Suggests brain modeling remains data-limited, contrasting with typical AI scaling trends where model size is primary.