KEYWORDS: Signal to noise ratio, Deep learning, Two photon imaging, Image enhancement, Imaging systems, Education and training, Two photon excitation microscopy, Signal processing, Neurons, Neural networks
We developed a high-speed two-photon volumetric imaging system with hundreds of axial layers that match a deep-learning denoising model to capture millisecond-level functional changes in individual neurons with high SNR. Compare with general deep-learning methods, the spatial information-based training method not only enhances SNR by 300% but prevents temporal distortion. Our proof-of-concept experiment focused on calcium dynamics in cerebellum Purkinje cells, revealing similar responses in the parallel dendritic layers, yet significant divergence in the somatic area. This sheds light on the intricate signal processing at individual neuron levels, validating our imaging system.
In this study, we have developed a small-footprint imaging framework identifying changes in the microvasculature of the mouse brain at different physiological states, including anesthesia, waking, and movement with the OCT angiography technique.
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