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.
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.