bioRxivNeurosciencePreprint
Decoding the Mouse Spinal Cord Locomotor Neural Network Using Tissue Clearing, Tissue Expansion and Tiling Light Sheet Microscopy Techniques
Ruili FengiD, Jiongfang Xie, Jing LüiD, Huijie HuiD, Yanlu Chen, Dongyue WangiD, Liang GaoiD
Abstract
Decoding a biological neural network requires the structural information regarding the spatial organization, dendritic morphology, axonal projection and synaptic connection of the neurons in the network. Imaging physically sectioned nervous tissues using electron microscopy (EM) has been the only method to acquire such information. However, EM is inefficient for imaging and reconstructing large neural networks due to the low throughput and inability to target neural circuits of interest by labeling specific neuron populations genetically. Here, we present a method to image large nervous tissues from the cellular to synaptic level with high throughput using tiling light sheet microscopy combined with tissue clearing and tissue expansion techniques. We describe the method, demonstrate its capability and explore its utility for decoding large biological neural networks by studying the spinal cord locomotor neural network in genetically labeled fluorescent mice. We show our method could advance the decoding of large neural networks significantly.
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