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Abstract-The mission of the Georgia State University BrainLab is to create and adapt methods of human-computer interaction that will allow brain-computer interface (BCI) technologies to effectively control real-world applications. Most of the existing BCI applications were designed largely for training and demonstration purposes. Our goal is to research ways of transitioning BCI control skills learned in training to real-world scenarios. Our research explores some of the problems and challenges of combining BCI outputs with human-computer interface paradigms in order to achieve optimal interaction. We utilize a variety of application domains to compare and validate BCI interactions, including communication, environmental control, neural prosthetics, and creative expression. The goal of this research is to improve quality of life for those with severe disabilities.Index Terms-Assistive technology, augmentive and assistive communication (AAC), brain-computer interface (BCI), direct-brain interface (DBI), environmental control, locked-in syndrome, neural prosthetics.

We describe the use of human cortical control signals to operate two assistive technology tools--a virtual keyboard speller and a computer-simulated digit. The cortical signals used for control are local field potentials recorded through an implanted neurotrophic electrode. In this system, the patients' cortical signals are transmitted wirelessly to a receiver and translated by computer software into either a computer cursor movement (for the virtual keyboard) or flexion of a cyber digit on a virtual hand. This report focuses on the progress of two subjects toward effective use of their "virtual" neuro-prosthetic devices to meet their assistive technology needs.

Functional theories posit that emotions are elicited by particular goal-related situations that represented adaptive problems and that emotions are evolved features of coordinated responses to those situations. Yet little theory or research has addressed the evolutionary aspects of these theories. We apply five criteria that can be used to judge whether features are adaptations. There is evidence that sadness, anger, and anxiety relate to unique changes in physiology, cognition, and behavior, those changes are correlated, situations that give rise to emotions are consistent, and emotions are complex. To date, there is little experimental evidence regarding whether discrete emotions resolve adaptive problems and do so relatively efficiently. Evidence supporting all criteria is required to claim that discrete emotions are evolved features.