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A growing corpus of experimental research demonstrates that neuroimaging data can be leveraged to improve the performance of artificial intelligence models, including reinforcement learning models in robotics. However, most existing studies have focused on vision, audition, language, or reward and error signals recorde...
It is hypothesized that neuroimaging data could open a window into elements of human cognition that are not accessible through observable actions, and it is argued that this additional knowledge could be used, alongside classical training data, to overcome some of the current limitations of foundation models.
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