PNRR AXOLOTL

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Bioretics won a PNRR Italian National Project denominated AXOns LOng Tracing via Lightsheet (AXOLOTL), CUP I19J24000230004

Mapping neuronal connectivity at the single-axon resolution remains one of the major technological challenges in contemporary neuroscience. Due to the peculiar shape of axons—which can extend across the entire brain yet have diameters smaller than a micron—a mapping system must be capable of analyzing very large volumes while simultaneously providing subcellular resolution. In this context, an optical imaging technique that has emerged over the past decade as a potential game changer is light-sheet microscopy, combined with chemical tissue clearing and expansion methods. One of the leading national and international research groups in this field is based at one of THE’s partners, namely the University of Florence (Department of Physics and Astronomy).

However, generating high-resolution images is not sufficient to solve the problem of axonal connectivity. From the datasets—which often reach several terabytes in size—it is necessary to extract a quantitative, numerical representation. Specifically, for each axon, it is necessary to move from a set of pixels to a vector-based representation in a three-dimensional reference system, enabling quantitative analyses and comparisons across subjects, and thus allowing knowledge to be extracted from the data. Unfortunately, current segmentation and tracing tools still require extensive manual intervention, making them unsuitable for large-scale analyses. For this reason, axonal mapping is currently limited to a few initiatives with substantial human and financial resources.

In this context, the goal of this project is to develop a software application for large-scale, automatic tracing of axonal fibers, primarily based on artificial intelligence.

Bioretics won a PNRR Italian National Project denominated AXOns LOng Tracing via Lightsheet (AXOLOTL), CUP I19J24000230004