Light sheet fluorescence microscopy for neuroscience
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Background: The functions of the central nervous system (CNS) rely on the interaction between large populations of neurons across different areas. Therefore, to comprehend CNS functions there is a need for imaging techniques providing access to the neuronal activity of large networks of neurons with very high spatiotemporal resolution. New method: Light sheet fluorescence microscopy (LSFM) is a very promising optical sectioning technique that allows volumetric imaging over many length scales while retaining high spatial resolution and minimizing photobleaching and phototoxicity. Results: The application of LSFM in neuroscience opened up the possibility of imaging in-vivo the development of the CNS and acquiring morphological images of whole cleared mammalian brains with sub-cellular resolution. The use of propagation invariant Bessel and Airy beams has shown potential for increasing the penetration depth in turbid neural tissues. Comparison with existing methods: The lack of temporal and/or spatial resolution of traditional neuroscience imaging techniques call attention to a need for a technique capable of providing high spatio temporal resolution. LSFM, which is capable of acquiring high resolution volumetric images is increasingly becoming an interesting imaging technique for neuroscience. Conclusions: The use of different LSFM geometries has shown the potential of this technique in acquiring in-vivo functional images of the CNS and morphological images of entire cleared mammalian brains. Further development of single objective LSFM implementations and fibre based LSFM combined with the use of propagation invariant beams could allow this technique to be used for in depth in-vivo imaging.
Corsetti , S , Gunn-Moore , F & Dholakia , K 2019 , ' Light sheet fluorescence microscopy for neuroscience ' Journal of Neuroscience Methods , vol. 319 , pp. 16-27 . https://doi.org/10.1016/j.jneumeth.2018.07.011
Journal of Neuroscience Methods
© 2018 Elsevier B. V. This work has been made available online in accordance with the publisher’s policies. This is the author created, accepted version manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at: https://doi.org/10.1016/j.jneumeth.2018.07.011
DescriptionWe thank the UK Engineering and Physical Sciences Research Council for funding through grants EP/R004854/1 and EP/P030017/1.
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