Towards a Center for Intelligent Brain Mapping
Principal Investigators: Zhi-Pei Liang (ECE), Bradley P. Sutton (BioE), Mark Anastasio (BioE), Volodymyr Kindratenko (NCSA), Aron K. Barbey (Neuroscience), and Tracey Wszalek (Beckman & Carle Foundation Hospital)
Co-investigators: Maria Jaromin (NCSA), Fan Lam (BioE), Yoram Bresler (CSL), Minh Do (ECE), Monica Fabiani (Psychology), Gabriele Gratton (Psychology), Mei Shen (Chemistry), Paul M. Arnold (Carle-Illinois COM), Bruce Damon (Carle-Illinois COM), and Gene Robinson (Carl Woese IGB)
Research Problem
The human brain is the most complex living structure in the universe, with over 100 billion neurons and the capability to create a vast network of connections. Unraveling the mysteries of the brain – how it works and what goes wrong when it is injured or diseased has been a dream of scientists and medical doctors for more than a century. The primary goal of this project is to launch an ambitious collaborative research effort to reveal the structural, functional, and molecular fingerprints of human brain function and diseases, by leveraging Illinois’ special strengths in neuroimaging, label-free molecular imaging, machine learning, and neuroscience.
Vision
Synergistic integration of modern deep learning with ultrafast high-resolution magnetic resonance spectroscopic imaging will provide an unprecedented capability to enable ultrafast high-resolution mapping of structural, functional and molecular fingerprints of the whole brain. Such a capability will transform how brain mapping is performed, yielding deeper insights and understanding of brain function and diseases.
Larger Impact
Brain diseases are among the most painful and debilitating disorders. The outcome of this project can significantly enhance our capability to address the unmet medical needs in accurately detecting and monitoring the treatment of these debilitating diseases. Synergistic integration of modern deep learning, biological modeling (of disease processes such as tumor growth or progression of Alzheimer’s disease), and physics modeling (of brain data acquisition) in the platform will provide new, long-desired computational capabilities for early detection of brain diseases, prediction of disease progression, and assessment of therapeutic efficacy.