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PyZebraScope: an open-source platform for brain-wide neural activity imaging in zebrafish

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Title:PyZebraScope: an open-source platform for brain-wide neural activity imaging in zebrafish
Creators Name:Barbara, R. and Nagathihalli Kantharaju, M. and Haruvi, R. and Harrington, K. and Kawashima, T.
Abstract:Understanding how neurons interact across the brain to control animal behaviors is one of the central goals in neuroscience. Recent developments in fluorescent microscopy and genetically-encoded calcium indicators led to the establishment of whole-brain imaging methods in zebrafish, which records neural activity across a brain-wide volume with single-cell resolution. Pioneering studies of whole-brain imaging used custom light-sheet microscopes, and their operation relied on commercially developed and maintained software that is not available globally. Hence it has been challenging to disseminate and develop the technology in the research community. Here, we present PyZebrascope, an open-source Python platform designed for neural activity imaging in zebrafish using light-sheet microscopy. PyZebrascope has intuitive user interfaces and implements essential features for whole-brain imaging, such as two orthogonal excitation beams and eye damage prevention. Its modular architecture allows the inclusion of advanced algorithms for microscope control and image processing. As a proof of concept, we implemented an automatic algorithm for maximizing the image resolution in the brain by precisely aligning the excitation beams to the image focal plane. PyZebrascope enables whole-brain neural activity imaging in fish behaving in a virtual reality environment with a stable high data throughput and low CPU and memory consumption. Thus, PyZebrascope will help disseminate and develop light-sheet microscopy techniques in the neuroscience community and advance our understanding of whole-brain neural dynamics during animal behaviors.
Keywords:Animals, Zebrafish
Publisher:Cold Spring Harbor Laboratory Press
Article Number:bioRxiv
Date:15 February 2022
Official Publication:https://doi.org/10.1101/2022.02.13.480249
Related to:
https://edoc.mdc-berlin.de/21387/Final version

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