Recent scienti¿c and technical advances enable the development of systems for creating novel interactions
with the central nervous system (CNS) that can induce bene¿cial plasticity. These systems, called adaptive
neurotechnologies, measure signals from the CNS, derive from these signals the state of the CNS, and adaptively
provide feedback that can restore, replace, enhance, supplement or improve CNS functions impaired by injury or
disease. Thus, they can provide powerful new therapies for stroke, head or spinal cord injury, cerebral palsy, and
other devastating disorders. For example, they can restore communication to people who have lost muscle control,
and they can enhance functional recovery for people with spinal cord injury or stroke.
The development of these technologies is impeded by the need for research groups to create specialized
real-time software, which is usually a lengthy, dif¿cult, expensive, and sometimes impractical task. Thus, realization
of these new technologies could be greatly facilitated by a robust and ¿exible software platform that supports
complex real-time interactions with the CNS throughout the development process, from the laboratory through
clinical testing. The goal of this proposal is to create this platform.
The central hypothesis is that, by creating this new platform and giving it to scientists, engineers, and clinicians,
this software platform will accelerate realization of adaptive neurotechnologies that reduce the devastating impact
of neurological disorders. This hypothesis is supported by the investigators' past experience and success in
creating and disseminating BCI2000, a software platform for brain-computer interfaces (BCIs), one category of
adaptive neurotechnologies. BCI2000 has supported scienti¿c and clinical studies reported in over 1000 papers.
This proposed project will transform BCI2000 into BCI2000+, a hardened, expanded, easy-to-use, and fully
documented software platform for a broad range of adaptive neurotechnologies. Aim 1 will create a reliable,
fail-safe, and fault-tolerant architecture, produce new functionalities for multimodal signal acquisition, real-time
processing and output generation, and user extensions. Aim 2 will produce new graphical tools for rapid system
prototyping, advanced signal and data visualization, comprehensive user-appropriate documentation, and auxiliary
tools for data management and of¿ine analysis. BCI2000+ will be optimized and validated through extensive in-lab
testing and through beta testing by other groups.
Achievement of these aims will produce BCI2000+, a software platform that supports new adaptive neurotech-
nologies from initial laboratory studies through clinical testing. This robust, ¿exible, and easily adopted platform
should encourage scientists, engineers, and clinicians to join in this exciting work; it should foster a collaborative
environment that enables diverse investigators to work together and complement each other. In sum, the work
proposed here will accelerate realization of novel adaptive neurotechnologies that enable scienti¿c investigation
and improve treatment for stroke, brain and spinal cord injury, and other devastating neurological disorders.