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Abstract We report a method for the phase reconstruction of an ultrashort laser pulse based on the deep learning of the nonlinear spectral changes induce by self-phase modulation. The neural networks were trained on simulated pulses with random initial phases and spectra, with pulse durations between 8.5 and 65 fs. The reconstruction is valid with moderate spectral resolution, and is robust to noise. The method was validated on experimental data produced from an ultrafast laser system, where near real-time phase reconstructions were performed. This method can be used in systems with known linear and nonlinear responses, even when the fluence is not known, making this method ideal for difficult to measure beams such as the high energy, large aperture beams produced in petawatt systems. 

Abstract Multiphoton microscopy has emerged as the primary imaging tool for studying the structural and functional dynamics of neural circuits in brain tissue, which is highly scattering to light. Recently, three-photon microscopy has enabled high-resolution fluorescence imaging of neurons in deeper brain areas that lie beyond the reach of conventional two-photon microscopy, which is typically limited to ~ 450 µm. Three-photon imaging of neuronal calcium signals, through the genetically-encoded calcium indicator GCaMP6, has been used to successfully record neuronal activity in deeper neocortical layers and parts of the hippocampus in rodents. Bulk-loading cells in deeper cortical layers with synthetic calcium indicators could provide an alternative strategy for labelling that obviates dependence on viral tropism and promoter penetration, particularly in non-rodent species. Here we report a strategy for visualized injection of a calcium dye, Oregon Green BAPTA-1 AM (OGB-1 AM), at 500–600 µm below the surface of the mouse visual cortex in vivo. We demonstrate successful OGB-1 AM loading of cells in cortical layers 5–6 and subsequent three-photon imaging of orientation- and direction- selective visual responses from these cells.