Deep-learning on-chip DSLM enabling video-rate volumetric imaging of neural activities in moving biological specimens

Abstract

Volumetric imaging of dynamic signals in a large, moving, and light-scattering specimen is extremely challenging, owing to the requirement on high spatiotemporal resolution and difficulty in obtaining high-contrast signals. Here we report that through combing a microfluidic chip-enabled digital scanning light-sheet illumination strategy with deep-learning based image restoration, we can realize isotropic 3D imaging of crawling whole Drosophila larva on an ordinary inverted microscope at single-cell resolution and high volumetric imaging rate up to 20 Hz. Enabled with high performances even unmet by current standard light-sheet fluorescence microscopes, we intoto record the neural activities during the forward and backward crawling of 1st instar larva, and successfully correlate the calcium spiking of motor neurons with the locomotion patterns.