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Scientists at Duke University have released a highly detailed model of connections in the mouse brain that could provide generations of neuroscientists new insights into brain circuits and origins of mental illness, such as depression and schizophrenia. The findings are published in the journal Cerebral Cortex.
Scientists conduct millions of experiments every year with mice, which have been genetically modified to mimic human disease. Having a far more precise model of the mouse brain will enhance knowledge about the connection between genetics and corresponding human disease, according to G. Allan Johnson, director of the Duke Center for In Vivo Microscopy.
“Interest in structural brain connectivity has grown with the understanding that abnormal neural connections play a significant role in neurologic and psychiatric diseases,” Johnson said. “Examining brain connectivity in small animals can help us better identify problems in the diseased brain, and apply that knowledge to humans.”
The scientists created the connectome, or map of brain circuitry, by performing an MRI scan of the brain of a healthy mouse at spatial resolution more than 100,000 times greater than that of a conventional clinical MRI. Data were acquired using diffusion MRI, which traces the pathways of nerve fibers called axons throughout the brain.
The accuracy of the connectome is determined by the spatial resolution and the number of different angles scanned. These new data are more than 1,000 times more precise than previous diffusion MRI scans of the mouse brain, Johnson said.
“Prior approaches to provide maps of the mouse brain have relied on fluorescent dyes injected into the brain,” Johnson said. “The brain is then cut in thin slices, digitized and put back together again in a computer. It’s a time-consuming process.”
Producing these high-resolution MRI images also has its challenges, he said. Scanning even a tiny mouse brain at such close detail creates a daunting amount of data that has in the past made such a project impractical, Johnson said.
But banks of high-powered computers have now allowed the scientists to capture and house the data and mathematically manipulate them to create the large 3-dimensional, digital models.
“This study mapping the connectivity of the mouse brain at high resolution could potentially have a profound and far-reaching effect on the neuroscience research community,” said Richard Conroy, Ph.D., director of the Division of Applied Science & Technology at the National Institute of Biomedical Imaging and Bioengineering. “Given the brain’s complexity, we are still unraveling how it is organized. This study dramatically improves our ability to resolve the connections between different regions of the brain, which could lead to more accurate neuroscience data and fewer inferences. This new map could potentially contribute to insights on neurological diseases and disorders.”
A colorful connectivity matrix accompanies the journal article (pictured), charting each region of the mouse brain and its probable connectivity to other brain structures. The researchers are currently building an online portal for scientists around the world to access the full directory of digital files to guide their own research into mouse neurocircuitry.
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In addition to Johnson, study authors include Evan Calabrese; Alexandra Badea; Gary Cofer; and Yi Qi.
Funding: The research was sponsored by the National Institute of Biomedical Imaging and Bioengineering (P41 EB015897) and the National Institute on Aging (K01 AG041211).
Source: Samiha Khanna – Duke University Medical Center Image Credit: The image is credited to Duke Medicine Original Research: Abstract for “A Diffusion MRI Tractography Connectome of the Mouse Brain and Comparison with Neuronal Tracer Data” by Evan Calabrese, Alexandra Badea, Gary Cofer, Yi Qi, and G. Allan Johnson in Cerebral Cortex. Published online June 5 2015 doi:10.1093/cercor/bhv121
A Diffusion MRI Tractography Connectome of the Mouse Brain and Comparison with Neuronal Tracer Data
Interest in structural brain connectivity has grown with the understanding that abnormal neural connections may play a role in neurologic and psychiatric diseases. Small animal connectivity mapping techniques are particularly important for identifying aberrant connectivity in disease models. Diffusion magnetic resonance imaging tractography can provide nondestructive, 3D, brain-wide connectivity maps, but has historically been limited by low spatial resolution, low signal-to-noise ratio, and the difficulty in estimating multiple fiber orientations within a single image voxel. Small animal diffusion tractography can be substantially improved through the combination of ex vivo MRI with exogenous contrast agents, advanced diffusion acquisition and reconstruction techniques, and probabilistic fiber tracking. Here, we present a comprehensive, probabilistic tractography connectome of the mouse brain at microscopic resolution, and a comparison of these data with a neuronal tracer-based connectivity data from the Allen Brain Atlas. This work serves as a reference database for future tractography studies in the mouse brain, and demonstrates the fundamental differences between tractography and neuronal tracer data.
“A Diffusion MRI Tractography Connectome of the Mouse Brain and Comparison with Neuronal Tracer Data” by Evan Calabrese, Alexandra Badea, Gary Cofer, Yi Qi, and G. Allan Johnson in Cerebral Cortex. Published online June 5 2015 doi:10.1093/cercor/bhv121
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