Prerequesites for symbiotic brain-machine interfaces

Recent advancements in the neuroscience and engineering of brain-machine interfaces are providing a blueprint for how new co-adaptive designs based on reinforcement learning change the nature of a user´s ability to accomplish tasks that were not possible using static methodologies. By designing adaptive controls and artificial intelligence into the neural interface, computers can become active assistants in goal-directed behavior and further enhance human performance. This paper presents a set of minimal prerequisites that enable a cooperative symbiosis and dialogue between biological and artificial systems.