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Novel Framework Reconstructs Neural Networks with High-Throughput Tools
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Novel Framework Reconstructs Neural Networks with High-Throughput Tools

Novel Framework Reconstructs Neural Networks with High-Throughput Tools
News

Novel Framework Reconstructs Neural Networks with High-Throughput Tools

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The conventional method of brain mapping based on transmission electron microscope (TEMs) images could take several decades to piece together. In this week's open-access journal PLoS Biology, research teams at the University of Utah and the University of Colorado at Boulder report technical advances that will dramatically accelerate the process for high-speed "color" ultrastructure brain mapping. The advances include software to build and view terabyte scale imagery acquired from conventional TEMs. "Our goals were to unleash a global network of electron microscopes and provide web-accessible imagery for battalions of brain network analysts," said Robert Marc, Director of Research for the Moran Eye Center at the University of Utah. "This changes the playing field for building brain map s from a few specialized laboratories to the desktops of biologists world-wide."

The new automation tools developed at the University of Colorado at Boulder, Center for 3D Electron Microscopy, allow capture of 25,000 TEM images weekly. In parallel, the Scientific Computing and Imaging Institute at the University of Utah developed software to automatically merge thousands of images into gigabyte-scale mosaics and align the mosaics into terabyte-scale volumes. Finally, teams at the Moran Eye Center developed TEM-compatible molecular probes and classification software to tag every cell with a molecular signature, creating "color" TEM imaging.

The study validated automation algorithms, molecular tagging, and the imaging workflow by exploring neuronal networks in the normal mammalian retina and genetic models of retinal degeneration. The authors also detailed a project to map all the connections in a large retinal volume. Over 92% of the 400,000-image volume has been built and should be complete by mid-April. Lead author James Anderson explains, "This technology lets the neuroscience field build circuitry blueprints for healthy neural tissues. We can compare diseased tissues to these blueprints to understand how they rewire the brain and use them to evaluate the effectiveness of treatments which aren't detectable with other methods."

The framework overcomes previous barriers to large-scale TEM and enables communal visualization with web-compliant viewers. This is a new way to explore traumatic brain injury, neurodegenerative diseases, and epilepsy. It also makes screening of genetic models practical. By combining these tools with advanced image processing, the questions that can be explored by TEM may be limited only by the imaginations of biologists.

http://biology.plosjournals.org/perlserv/?request=get-document&doi=10.1371/journal.pbio.1000074

 

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