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Understanding how networks of neurons process information is one of the key challenges in modern neuroscience. A necessary step to achieving this goal is to be able to observe the dynamics of large populations of neurons over a large area of the brain. Light-field microscopy (LFM), which uses a type of scanless microscope, is a particularly attractive candidate for high-speed 3D imaging. It captures volumetric information in a single snapshot, allowing volumetric imaging at video frame rates. Specific features of imaging neuronal activity using LFM call for the development of novel machine learning approaches that fully exploit the priors embedded in physics and optics models.

Light-Field Microscopy for the Optical Imaging of Neuronal Activity: When model-based methods meet data-driven approaches