Mesoscopic microscopy for ultra-high speed and large-scale volumetric brain imaging

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PROJECT SUMMARY The brain is built on billions of neural connections in a highly organized 3D hierarchy. At the same time, neural activity is highly dynamics that requires kilohertz imaging rate to capture action potentials and sub-threshold voltage signals, the fundamental bit for neural communication. While the recent advent of genetically encoded voltage indicators (GEVIs) makes it possible to optically record the neural membrane voltage, the technical challenges are profound in imaging millimeter-scale volumetric voltage imaging at kilohertz with cellular resolution. In this proposal, we aim to address the challenges by developing a one-photon mesoscopic (i.e. millimeter scale field of view, FOV) volumetric voltage imaging, using mesoscopic oblique plane microscopy (Meso-OPM). Our technique will image >1.8 mm2 FOV, >0.1 mm depth penetration at 1 KHz, capable of recording voltage signals across an entire nervous system of a Zebrafish larva. The bright and stable GEVIs Voltron with JF525 dye will be used in our proposed work. Meso-OPM is a variant of light sheet microscopy (LSM), with a single primary objective lens instead of two in conventional LSM. The simplified optical design allows 1) leveraging high photon efficiency in LSM; 2) integrating ultra-fast passive optical scanning to achieve >1 MHz frame rate; and 3) flexible optical designs for millimeter FOV and cellular resolution. In addition to the technical challenges for large-scale ultrafast 3D imaging, the effective data processing pipeline for massive data is also highly desirable. To this end, we propose a robust and efficient deep learning framework to perform self- supervised 4D denoising and neuron segmentation. The pipeline enable massive data processing at 10 volume per second for the downstream neuroscience studies. Finally, to demonstrate the utility of proposed techniques, we will image Zebrafish in response to optic flow by a drifting grating visual stimuli. We will identify neural circuitry responsible to the motion compensation to the optic flow (i.e. maintaining body position when presented drifting grating) from eyes all the way to spinal cord. Altogether, this proposal will greatly improve our capability of dissecting large-scale neural circuitry, and the sub-sequent modeling and creation of artificial neural circuits.