MRI Corticography (MRCoG)

Principal Investigator: David Alan Feinberg
Helen Wills Neuroscience Institute
Title: “MRI Corticography (MRCoG): Micro-scale Human Cortical Imaging”
BRAIN Category: Next Generation Human Imaging (RFA MH-14-217)

To image the activity and connections of the brain’s cortex on a micro scale – with dramatically higher resolution than existing scanners – Dr. Feinberg’s group will employ high sensitivity MRI coils that focus exclusively on the brain’s surface.

NIH Webpages

Project Description

MRI is the only technology that can image the connectivity of the human brain in vivo and non-invasively. However, neither BOLD fMRI nor diffusion-based fiber tracking has been able to break the barrier of 1-mm voxel spatial resolution. Yet, 1-mm voxel contains roughly 50,000 neuronal cells and the human cortex is less than 5 mm thick. The disparity between the spatial scales has thus created a large gap between MRI studies of the whole brain and optical imaging and cell recordings of groups of neurons. The overarching objective of this proposal is to bring noninvasive human brain imaging into the microscale resolution and begin to bridge studies of neuronal circuitry and network organization in the human brain. Our breakthrough technology, termed MR Corticography (MRCoG), will achieve dramatic gains in spatial and temporal resolutions by focusing exclusively to the cortex. Higher-sensitivity coil sensors will be designed that tailor to the superficial volume of the brain MRCoG will also be used to map intracortical axonal connectivity, overcoming a fundamental resolution limit inherent to all in vivo human neuronal fiber tractography to date by replacing diffusion imaging with a novel susceptibility contrast mapping of axon fibers. Innovative imaging pulse sequences will be designed to complement the high-sensitivity coil arrays to achieve higher spatial resolution in the neocortex. The improved capabilities of these sensors will be further exploited using new, vastly more efficient spatial multiplexed and temporal multiplexed image acquisition to further accelerate scanning by taking advantage of spatiotemporal sparsity. In summary, the proposed research will create a novel technology for imaging the human brain’s neocortex with barrier-breaking resolution and contrast. MRCoG will facilitate the integration between in vivo non-invasive human-brain MRI and cellular and genetic imaging techniques. If successful, it will fundamentally transform our ability to study the human brain. Because it is based on MRI, MRCoG can be readily translated to patient care, providing potential high impact in the care of mental health, traumatic brain injuries, epilepsy among many other debilitating brain diseases and disorders.

Public Health Relevance Statement

If successful, the new technology developed in this project will dramatically improve our ability to visualize the structures and functions of human brain cortex. As a new research tool, it can not only transform the understanding of networks within our brain, but also provide potential high impact in the care of mental health, traumatic brain injuries, epilepsy among many other debilitating brain diseases and disorders.

NIH Spending Category

Bioengineering; Brain Disorders; Clinical Research; Diagnostic Radiology; Epilepsy; Injury (total) Accidents/Adverse Effects; Injury – Trauma – (Head and Spine); Injury – Traumatic brain injury; Networking and Information Technology R&D; Neurodegenerative; Neurosciences

Project Terms

Axon; base; blood oxygen level dependent; Brain; Brain Concussion; Brain Diseases; Brain imaging; brain volume; Caring; Cells; clinical application; Cognition Disorders; Complement; Computational algorithm; Computer Simulation; Coupling; data acquisition; Data Set; density; design; Diagnostic; Diffusion; Diffusion Magnetic Resonance Imaging; Disease; Electrocorticogram; Epilepsy; Evaluation; Fiber; Functional Magnetic Resonance Imaging; Genetic; Geometry; Goals; Human; Image; image processing; Image Reconstructions; Imaging Techniques; improved; in vivo; innovation; Life; Magnetic Resonance Imaging; Maps; Measurement; Mental Depression; Mental Health; Methods; Neocortex; neocortical; Network-based; neural circuit; neuronal circuitry; Neurons; Neurosciences; new technology; novel; optic imaging; optogenetics; Pathway Analysis; Patient Care; Patients; Penetration; Peripheral; Physiologic pulse; Positron-Emission Tomography; Predisposition; Process; prototype; public health relevance; radiofrequency; Research; Resolution; Scanning; Seizures; sensor; Shapes; Signal Transduction; Slice; spatiotemporal; Speed (motion); Structure; System; Techniques; Technology; Testing; Thick; Three-Dimensional Imaging; tool; Translating; Traumatic Brain Injury; Validation; validation studies; white matter

Press Release

From UC Berkely News 9/30/15

Surface imaging of the brain

David Feinberg, a UC Berkeley adjunct professor of neuroscience, and collaborators at the University of California, San Francisco, Harvard and Duke universities will receive $1.4 million over three years from NIMH to increase the detail or spatial resolution of magnetic resonance imaging (MRI) more than 30 times over today’s most powerful MRI scanners.

smaller coils provide more detail about the surface of the brain
Smaller MRI coils provide much more detail about the surface of the brain, where thinking and learning take place, but less detail about the interior, as illustrated in these simulated vews from the top of the head on the right. David Feinberg image.


“Just as with the Hubble Space Telescope, with clearer and more detailed images you discover new things,” said Feinberg, a physicist who has worked for decades to improve the speed and clarity of MRI imaging. “Assuming we achieve such higher resolution, it will open the door to many new experiments to study brain circuitry.”

Functional MRIs (fMRI) use magnetic fields and radio waves to map areas of the brain that are actively working, allowing neuroscientists or psychologists to pinpoint areas involved in specific tasks, ranging from reading or recognizing faces to emotions such as fear or love. The faint signals from molecules in the brain are typically detected by coils of wire arranged around the head, but these receiver coils need to be large – eight centimeters (3 ¼ inches) in diameter in state-of-the-art machines with 32 coils – in order to record from deep in the brain’s interior.

Functional MRI is sometimes critically referred to as “blobology,” he said, because identifiable regions of brain activity consist of hundreds of thousands of nerve cells, providing only a blobby average of what is happening at any one time.

If you want to study thinking and learning, however, you need focus only on the outer three millimeters of the brain, the grey matter or cortex, Feinberg said.

“The gray matter at the surface of the brain is where the neuron cell bodies and nerve networks lie, so that is where the action is,” he said. “To probe that thin layer, we will use many smaller coils – each with greater sensitivity – to gather more detail in the brain cortex close to the coil.“

The new technique, called MR Corticography (MRCoG) or cortical MRI, would reveal changes in much smaller regions, identifying the cellular layers of the cortex. They hope to see features as small as 200 microns across, or about twice the width of a human hair.

“MR Corticography … synergistically and cleverly combines cutting edge hardware and software technologies that are being pursued by the various experts on this project to allow us to achieve the very challenging goal of creating microscale MR imaging,” said colleague Kawin Setsompop, an assistant professor of radiology at Harvard Medical School and the Athinoula A. Martinos Center for Biomedical Imaging at Massachusetts General Hospital.

“One aim of the project is to develop new technologies to map nerve fibers and brain connectivity,” said Chunlei Liu, assistant professor of radiology at the Brain Imaging and Analysis Center at Duke University School of Medicine.

“This could help bridge the gap between the detail we see now in humans with fMRI and what is going on at the level of the computational networks within the cortex,” Feinberg said.

Pratik Mukherjee, a clinical neuroradiologist and professor of radiology and bioengineering at UCSF and the San Francisco Veterans Administration hospital pointed to many clinical applications of the MRCoG technology, including traumatic brain injury, autism and epilepsy.

“The improved clarity of the cortical imaging promises to improve the diagnosis and surgical evaluation of many forms of epilepsy by better identifying the abnormal cellular architecture in the gray matter that triggers seizures,” Mukherjee said. “This should help the neurosurgeon to resect all of the abnormal region and thereby prevent or at least greatly reduce any further seizures, while sparing nearby normal brain areas that would result in postoperative deficits if removed.”

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