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Technologies for imaging neural activity in large volumes

Nature Neuroscience volume 19, pages 1154–1164 (2016)Cite this article

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Abstract

Neural circuitry has evolved to form distributed networks that act dynamically across large volumes. Conventional microscopy collects data from individual planes and cannot sample circuitry across large volumes at the temporal resolution relevant to neural circuit function and behaviors. Here we review emerging technologies for rapid volume imaging of neural circuitry. We focus on two critical challenges: the inertia of optical systems, which limits image speed, and aberrations, which restrict the image volume. Optical sampling time must be long enough to ensure high-fidelity measurements, but optimized sampling strategies and point-spread function engineering can facilitate rapid volume imaging of neural activity within this constraint. We also discuss new computational strategies for processing and analyzing volume imaging data of increasing size and complexity. Together, optical and computational advances are providing a broader view of neural circuit dynamics and helping elucidate how brain regions work in concert to support behavior.

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Figure 1: Optical access and basic optical layout of two-photon laser scanning microscopy.
Figure 2: Scan engine and objective determine imaging FOV.
Figure 3: 2D and 3D scanning strategies.
Figure 4: Sampling strategies.
Figure 5: Aberration and scattering limit imaging depth.

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Acknowledgements

We thank J. Kuhl and A. Chen for help with illustrations, C. Xu for providing the high-resolution version of Figure 5c and N. Sofroniew for providing comments. N.J. and J.F. are supported by Howard Hughes Medical Institute. S.L.S. is supported by grants from the Human Frontier Science Program (CDA00063/2012 and RGP0027/2016), the National Science Foundation (1450824), the Whitehall Foundation, the Klingenstein Foundation, the McKnight Foundation, the Simons Foundation (SCGB 325407SS) and the National Institutes of Health (R01NS091335 and R01EY024294).

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Authors and Affiliations

  1. Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA

    Na Ji & Jeremy Freeman

  2. Department of Cell Biology and Physiology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA

    Spencer L Smith

  3. Neuroscience Center, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA

    Spencer L Smith

  4. Carolina Institute for Developmental Disabilities, University of North Carolina School of Medicine, Chapel Hill, North Carolina

    Spencer L Smith

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  1. Na Ji
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Correspondence to Na Ji, Jeremy Freeman or Spencer L Smith.

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Ji, N., Freeman, J. & Smith, S. Technologies for imaging neural activity in large volumes. Nat Neurosci 19, 1154–1164 (2016). https://doi.org/10.1038/nn.4358

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