Principal Investigator: Allen W Song
Duke Institute for Brain Sciences
Title: “Path Toward MRI with Direct Sensitivity to Neuro-Electro-Magnetic Oscillations”
BRAIN Category: Next Generation Human Imaging (RFA MH-14-217)
Dr. Song’s group will develop a scanner technology sensitive enough to image brain activity in high resolution by directly tuning in the electromagnetic signals broadcast by neurons.
In response to the NIH RFA-MH-14-217 on “Planning for Next Generation Human Brain Imaging”, we propose a comprehensive plan to organize the much needed technological resources and interdisciplinary research team for developing the next generation MRI technology that can directly detect neuroelectric activities in the human brain with a high spatial and temporal resolution, using scanners with the 3 Tesla magnetic field strength that is accessible by the majority of neuroimaging researchers. Through our encouraging preliminary investigations, we have determined that it is possible to precisely map brain activities by directly sensitizing the MRI signal to the neuro-electro-magnetic oscillations (NEMO). At the same time, we have also identified key challenges in MRI hardware, acquisition methods, and contrast mechanisms to fully enable this approach. We will address these challenges by organizing three innovative technical cores (in the form of Technical Aims) for the purpose of enabling an ultra-uniform magnetic field throughout the brain to ensure a robust detection of the NEMO signal, reaching ultra-high spatial resolutions that can resolve fine-grained cortical microstructures, and building a non-invasive human brain-machine interface (BMI) that models and classifies the functional neuroimaging signals and drives an attached robotic exoskeleton. To establish convincing evidences toward a direct and sensitive MRI detection of neuroelectric activity, and based on our solid technical foundation, we also propose four innovative pilot projects (in the form of Scientific Aims) to construct a static neural networ with causal information using high-resolution MRI, to investigate dynamic NEMO signals in vivo with enhanced sensitivity during both driven and intrinsic neuronal oscillations, and to model and classify the dynamic neuroimaging signals and to replicate and validate the human behavior in the robotic exoskeleton through our non-invasive human BMI. To help evaluate our research progress and receive critical input from researchers and leaders in the brain research community, we will organize annual workshops coordinated by our interdisciplinary research team and our scientific advisory committee. We anticipate that through these comprehensive planning and research activities, we will be able to define a clear path to reach the next generation human brain imaging technology that can precisely, non-invasively, and unambiguously map brain activities with unprecedented spatial and temporal resolution.
Public Health Relevance Statement
The emergence of hemodynamically based functional MRI (fMRI) for non-invasively imaging human brain activity has made it the preeminent method to study human brain function. Despite its explosive growth in the past two decades, however, fMRI today is still an indirect measure of functional electrical brain activity, limited by spatial dispersions and temporal delays from the hemodynamic modulation. Building on the advances in high-resolution structural and functional MRI and innovative contrast mechanisms developed in our laboratory in the past several years, we propose to build the next generation MRI methodology that can directly, and precisely image neuroelectric activities in the human brain. We expect that our comprehensive plan will carve a clear path for developing and validating this innovative neurotechnology, which will enable neuroscience researchers to investigate human brain structure and function with unprecedented spatial and temporal resolution and true neuronal sensitivity, in both healthy individuals and in those with neural and psychiatric disorders.
NIH Spending Category
Assistive Technology; Bioengineering; Brain Disorders; Clinical Research; Diagnostic Radiology; Neurosciences
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