Self-guided Microrobotics for Automated Brain Dissection

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Neural precursor cells (NPCs) are neural stem cells and their progeny, which are multipotent, self-renewing cells that are responsible for building the fundamental components of the vertebrate central nervous system during embryonic development. Notably, NPCs persist into the mature brain as very rare cells that continue to generate new neurons throughout the lifetime of the organism. Intensive study of these precious cells could lead to a watershed moment in the field of neurobiology and the development of regenerative therapies to treat Alzheimer's disease, dementia, and traumatic brain injury. However, our ability to harness the therapeutic potential of NPCs is limited by the practical difficulty of identifying and collecting them for analysis. Current methods require painstaking manual microdissection of neural tissue followed by cell sorting methods which, in addition to requiring large samples sizes (and thus large quantities of tissue) also often fail to distinguish between NPCs and other cells expressing the same biomarkers.This highly interdisciplinary project brings together researchers with expertise in artificial intelligence (AI), robotics, engineering and neuroscience to create a new automated microsurgical platform which will be applied to identify and collect NPCs from brain tissues. By exploiting the capacity of deep learning approaches to detect features in complex data sets we will develop two new image-guided microsurgery tools: a microrobotic resector capable of carefully excising the small region of brain tissue (the SVZ) within which NPCs are found and microrobotic cell collector, capable of efficiently harvesting individual cells for further study and analysis using a coordinated array of optoelectronic microrobots. When then aim to integrate these two systems into a single, unique robotic microsurgery platform.The new system will be applied to collect and analyse NPCs from different brain tissues. In particular, we propose to analyse the sex-dependent differences in NPCs phenotypes, which have been reported in previous research. As well as transforming our capacity for collection of NPCs and likewise supporting the development of new regenerative therapies, we believe this approach will provide a powerful new method for a wide range of microsurgery applications. Altogether, we will use these results to simulate debate among the related engineering, scientific and wider public communities to shape a new international multi-disciplinary network focusing on challenges with regenerative medicine i.e. providing new case studies for govt. policy and further investment for AI-driven healthcare applications.