A Virtual Reality Simulator to Study VLSBA and Test Brain-Actuating Technologies

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DESCRIPTION Abstract: For the past 25 years, my research has focused on the investigation of the basic neurophysiological principles that allow neural circuits in the mammalian brain to generate sensory, motor, and cognitive behaviors. To pursue this goal, my laboratory has developed a series of highly innovative experimental approaches that combine electrophysiological, genetic, pharmacological, behavioral, computational, and engineering tools. Utilizing those, our laboratory has pioneered a revolutionary paradigm known as brain-machine interfaces (BMIs). Using BMIs, we have demonstrated that non-human primates and human subjects can effectively use their brain-derived electrical activity to directly control the movements of complex artificial devices, such as computer tools and prosthetic limbs. Yet, BMI research has barely touched the enormous biomedical potential that brain-actuating technologies will likely have in the future of both basic and clinical neuroscience. To start probing this future, I propose to develop the first shared brain-controlled virtual reality environment (BC-VRE) designed to investigate the dynamic properties of very-large scale brain activity (VLSBA) and the full potential of brain-actuating technologies for treating neurological disorders. The core of this virtual reality simulator will be formed by interfacing modern electrophysiological, magnetoenecephalographic (MEG), and brain imaging devices to a supercomputer cluster capable of rendering a virtual reality environment in which all constituent elements, including a variety of computational and robotic tools, and even virtual bodies, can be directly controlled by the VLSBA of interacting subjects. Initially, VLSBA will be obtained using a new method for mega-channel (up to 100,000 single neurons) recordings in non-human primates. Later on, the BC-VRE will also accept local or remote MEG/MRI data from human subjects. The BC-VRE will be initially used to: (1) measure how artificial tools are assimila