By explicitly linking reinforcement-driven human neuroplasticity with gradient-based decoder optimization, the framework unifies biological trial-and-error learning with mathematical machine learning loops.
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By explicitly linking reinforcement-driven human neuroplasticity with gradient-based decoder optimization, the framework unifies biological trial-and-error learning with mathematical machine learning loops.
