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  • Journal article
    Quicke P, Song C, McKimm EJ, Milosevic MM, Howe CL, Neil M, Schultz SR, Antic SD, Foust AJ, Knopfel Tet al., 2019,

    Single-neuron level one-photon voltage imaging with sparsely targeted genetically encoded voltage indicators

    , Frontiers in Cellular Neuroscience, Vol: 13, ISSN: 1662-5102

    Voltage imaging of many neurons simultaneously at single-cell resolution is hampered by the difficulty of detecting small voltage signals from overlapping neuronal processes in neural tissue. Recent advances in genetically encoded voltage indicator (GEVI) imaging have shown single-cell resolution optical voltage recordings in intact tissue through imaging naturally sparse cell classes, sparse viral expression, soma restricted expression, advanced optical systems, or a combination of these. Widespread sparse and strong transgenic GEVI expression would enable straightforward optical access to a densely occurring cell type, such as cortical pyramidal cells. Here we demonstrate that a recently described sparse transgenic expression strategy can enable single-cell resolution voltage imaging of cortical pyramidal cells in intact brain tissue without restricting expression to the soma. We also quantify the functional crosstalk in brain tissue and discuss optimal imaging rates to inform future GEVI experimental design.

  • Journal article
    Schultz SR, Copeland CS, Foust AJ, Quicke P, Schuck Ret al., 2016,

    Advances in two-photon scanning and scanless microscopy technologies for functional neural circuit imaging

    , Proceedings of the IEEE, Vol: 105, Pages: 139-157, ISSN: 0018-9219

    Recent years have seen substantial developments in technology for imaging neural circuits, raising the prospect of large-scale imaging studies of neural populations involved in information processing, with the potential to lead to step changes in our understanding of brain function and dysfunction. In this paper, we will review some key recent advances: improved fluorophores for single-cell resolution functional neuroimaging using a two-photon microscope; improved approaches to the problem of scanning active circuits; and the prospect of scanless microscopes which overcome some of the bandwidth limitations of current imaging techniques. These advances in technology for experimental neuroscience have in themselves led to technical challenges, such as the need for the development of novel signal processing and data analysis tools in order to make the most of the new experimental tools. We review recent work in some active topics, such as region of interest segmentation algorithms capable of demixing overlapping signals, and new highly accurate algorithms for calcium transient detection. These advances motivate the development of new data analysis tools capable of dealing with spatial or spatiotemporal patterns of neural activity that scale well with pattern size.

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