Connecting Brain and Machine

Artificial intelligence coupled with digitally connected technologies are becoming more self-evident. These developments indicate an increasing symbiosis between human and machine, referring to a new phase of interaction-symbiotic intelligence. In this vein, the human-centred development of technologies is becoming more and more important. The detection of user's mental states, such as cognitive processes, emotional or affective reactions, offers great potential for the development of intelligent and interactive machines. Neurophysiological signals provide the basis to estimate many facets of subtle mental user states, like attention, affect, cognitive workload and many more. This has led to extensive progress in brain-based interactions-Brain-Computer Interfaces (BCIs). While most BCI research aims at designing assistive, supportive or restorative systems for severely disabled persons, the current discussion focuses on neuroadaptive control paradigms using BCIs as a strategy to make technologies more human-centred and also usable for non-medical applications. The primary goal of our neuroadaptive technology research agenda is to consistently align the increasing intelligence and autonomy of machines with the needs and abilities of the human-a human-centred neuroadaptive technology research roadmap. Due to its far-reaching social implications, our research and developments do not only face technological but also social challenges. If neuroadaptive technologies are applied in non-medical areas, they must be consistently oriented to the needs and ethical values of the users and society.