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Computational models predict neural activity for re-establishing connectivity after stroke or injury

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Researchers at The Hong Kong University of Science and Technology (HKUST) School of Engineering have developed a novel reinforcement learning–based generative model to predict neural signals, creating an artificial information pathway that effectively bypasses damaged brain areas. This research opens up new possibilities for neural rehabilitation in patients suffering from motor or cognitive impairments caused by conditions such as stroke or spinal cord injury.


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