I did not have the time to read the 38 page pre-print research paper, but the abstract sounds interesting! This research was done at the Paul G. Allen School of Computer Science and Engineering. According to the authors it will appear as a chapter in the forthcoming Handbook of Neuroengineering.
"... Brain co-processors can be used for a range of applications, from inducing Hebbian plasticity for rehabilitation after brain injury to reanimating paralyzed limbs and enhancing memory. A key challenge is simultaneous multi-channel neural decoding and encoding for optimization of external behavioral or task-related goals. We describe a new framework for developing brain co-processors based on artificial neural networks, deep learning and reinforcement learning. These "neural co-processors" allow joint optimization of cost functions with the nervous system to achieve desired behaviors. ..."
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