High-Resolution 3D Mouse Brain Map For Neuroscience Researchers

Researchers at the Allen Institute in Seattle have created a 3D Mouse Brain Atlas, which functions as a spatial map of the brain and allows neuroscientists to contextualize their results based on specific brain landmarks. Strikingly, the resolution of the map is so high that it is possible to locate individual cells, providing an enormous amount of information about the structure and nature of the mouse brain. This tool could be very useful for neuroscientists using mouse brains to study the basis and mechanisms of neurological diseases, and develop new treatments.

Laboratory mice are commonly used in biomedical research, including research into neurological diseases. The mouse brain serves as a proxy for human brains in various models of human neurological disease. However, just like our own brains, the mouse brain is extremely complex and contains hundreds of specific regions, and approximately 100 million cells. Contextualizing the results of neuroscience studies, and comparing results between studies requires a map to make sense of this complex structure.

“In the old days, people would define different regions of the brain by eye. As we get more and more data, that manual curation doesn’t scale anymore,” explained Lydia Ng, a researcher involved in the project. “Just as we have a reference genome sequence, you need a reference anatomy.”



The brain atlas is based on the average brain anatomy of 1,700 laboratory mice, and these data have been meticulously assembled into a 3D rendering of the mouse brain. The tool allows researchers to conduct whole brain studies, and can incorporate various types of data, such as neuronal activity, allowing researchers to compare numerous datasets.

In the future, as additional information about the mouse brain comes to light, the researchers aim to construct further versions of the brain atlas using machine learning to avoid the work involved in manually assembling the current 3D model.

“As we know now, atlases should be evolving and living resources, because as we learn more about how the brain is organized, we will need to make updates,” said Julie Harris, another researcher involved in the project. “Building atlases in an automatic, unbiased way is where the field is likely moving.”

See a flythrough of the mouse brain model in the video below:


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