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From these laws we derive relative value and exchange rates between brain samples and task samples, quantifying how much extra task samples neural data is worth as a function of task-brain alignment, neural and task noise, latent dimension, and","title":"How Much is Brain Data Worth for Machine Learning?","url":"https://arxiv.org/abs/2605.09243","vendor":"arxiv_cs_ai"},"summary":"arXiv:2605.09243v1 Announce Type: new \nAbstract: If a person can solve a task, can measuring their brain make it easier to train a model to solve that task too? Recent NeuroAI work suggests that supplementing task training with neural recordings can modestly improve model performance and robustness. However, it is unclear when there should be a benefit from using neural data and how much benefit to expect. We formulate this question mathematically, and begin to address it theoretically using a simple, analytically tractable linear gaussian model of task targets and neural recordings. 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