This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5)
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There are currently over two million people in the United States suffering from various degrees of paralysis with an additional eleven thousand new cases of spinal cord injury each year. A means to rehabilitate these individuals would thus have tremendous economic and social impact. The brain-computer interface has been developed as a means to 'read' the minds of these individuals and translate these thoughts into actions performed via a computer, which aims at restoring function in paralytics by providing the brain with new output pathways.
The long-term goal of this project is to develop a novel non-invasive brain-computer interface system, which can perform complex tasks reliably and efficiently. The availability of such a system would have a significant impact in aiding patients with neurological disorders that cause significant impairment in mobility. The specific objective of the project is to use functional magnetic resonance imaging (MRI) and electroencephalogram (i.e. brain wave) recordings to provide a solid base of knowledge regarding the individual signatures associated with motor imagery tasks in order to significantly improve the design and implementation of motor imagery-based brain-computer interface systems. The specific aims of the project are to: 1) Investigate the spatial co-localizations between neural and hemodynamic responses associated with various motor imagery tasks; 2) Develop ultra-sensitive spatiotemporal imaging methods suited for imaging 'imagery' brain activity; 3) Develop and evaluate a novel multi-dimensional brain-computer interface system based on individual signatures extracted from the space, time and frequency domains of brain waves.
Intellectual Merits: The proposed research tackles a fundamental scientific challenge in converting 'thoughts' into actions through noninvasive measurements. A key component of the motor imagery-based brain-computer interface systems is to extract sensitive signatures in which human intentions are best encoded. Currently, such signatures are mainly based on information processing of scalp-recorded brain waves at the sensor space, which require significant training by the subject to achieve control of a multi-dimensional environment. Scalp-recorded brain waves lack specificity and the relationship between neuronal firing associated with 'intentions' and the recorded brain waves remains ambiguous. The transformative nature of the proposed research is to map the 'intentions' of individuals directly over the cortex where neural information processing is physically being performed. This highly innovative approach will be realized by establishing one-on-one mapping during imagination of a variety of movement tasks through the use of functional MRI and brain wave source imaging. The proposed data-driven approach enables rational fusing of functional MRI signals and brain waves, leading to ultra-sensitive means imaging the complex patterns of 'thoughts' signals. The successful completion of the proposed research will greatly expand the understanding of the neural mechanisms of motor imagery, and lead to the development of a transformative noninvasive multi-dimensional brain-computer interface system, which would have significantly enhanced specificity, efficiency, and reliability.
Broader Impacts: The proposed project has the potential for having major broad impacts in several areas: a) Societal: There are currently over two million people in the United States suffering from various degrees of paralysis. The proposed research promises to lead to highly complex noninvasive brain-computer interface systems, which may significantly aid in the clinical rehabilitation in this group of patients, benefiting public health and the economy. b) Technical: The proposed research addresses a significant problem in science - decoding signals related to 'thoughts' to control devices. The proposed research may make a significant contribution to neuroscience, rehabilitation engineering, control theory, signal processing, and imaging science. c) Enhancement of infrastructure for research and education: The proposed study will help strengthen collaborations among biomedical engineers, neuroscientists, and imaging scientists, and provide unique opportunities for interdisciplinary training of graduate students, postdoctoral fellows, and undergraduate students, including minority and female students. d) Knowledge dissemination: The findings will be broadly disseminated to other researchers in the field including scholarly publications and website dissemination of software codes.
