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Automated, all-optical cranial surgery for transcranial imaging of mouse brain


The recent developments of neuroscience have brought us a deeper understanding of the mammalian brain. One of the challenges imposed in neuroscience is to access the brain, with minimal disruption to the neural tissue. The current technologies of using mechanical tools to remove skulls bring both logistical and physiological challenges, as they are labor intensive procedures that are difficult to master. To address this issue, a novel, automated surgical technique has been developed in this dissertation project. In order to address the issue of automating cranial surgeries, we use ultrafast, nonlinear optics imaging techniques to detect and remove bone. First, applications of the imaging techniques in skull and neural tissue are investigated. Then, the experimental setup and its configuration for automated surgery are studied. Finally, the surgical technique is used for creating an in vivo transcranial window in a mouse skull. The optical quality of the transcranial window is examined via in vivo imaging of the vasculature and blood flow. The viability of the brain tissue after the surgery and imaging is assessed using biomarkers for immunohistochemistry. This dissertation establishes a way to automate sequences of in vivo cranial surgery for mouse, using nonlinear optics as feedback and as cutting tools. Direct application of this technique includes in vivo craniotomy and making micro- holes for electrode insertion

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