June 2022
Volume 63, Issue 7
Open Access
ARVO Annual Meeting Abstract  |   June 2022
Light-sheet imaging of large-scale neural population activity in the retina.
Author Affiliations & Notes
  • Suva Roy
    Neurobiology, Duke University School of Medicine, Durham, North Carolina, United States
  • Depeng Wang
    Biomedical Engineering, Duke University Pratt School of Engineering, Durham, North Carolina, United States
  • Marija Rudzite
    Neurobiology, Duke University School of Medicine, Durham, North Carolina, United States
  • Miranda Scalabrino
    Neurobiology, Duke University School of Medicine, Durham, North Carolina, United States
  • Yiyang Gong
    Biomedical Engineering, Duke University Pratt School of Engineering, Durham, North Carolina, United States
  • Alexander Sher
    Physics, University of California Santa Cruz Division of Physical and Biological Sciences, Santa Cruz, California, United States
  • Greg Field
    Neurobiology, Duke University School of Medicine, Durham, North Carolina, United States
  • Footnotes
    Commercial Relationships   Suva Roy None; Depeng Wang None; Marija Rudzite None; Miranda Scalabrino None; Yiyang Gong None; Alexander Sher None; Greg Field None
  • Footnotes
    Support  NIH Grant 1R34NS111645-01
Investigative Ophthalmology & Visual Science June 2022, Vol.63, 1162. doi:
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      Suva Roy, Depeng Wang, Marija Rudzite, Miranda Scalabrino, Yiyang Gong, Alexander Sher, Greg Field; Light-sheet imaging of large-scale neural population activity in the retina.. Invest. Ophthalmol. Vis. Sci. 2022;63(7):1162.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : The visual signal entering the mouse retina is distributed across ~14 different bipolar cell (BC) types and then across ~40 different retinal ganglion cell (RGC) types. Each of these cell types are specialized to perform a specific computation for extracting relevant features of the visual world. To understand how these computations are implemented in neural circuits, we need to measure neural population activity in distinct BC and RGC types. Existing technologies are limited in scope in measuring population neural activity across synaptic tiers.

Methods : We have developed a single-photon light-sheet imaging system for measuring large-scale population activity of retinal cells. We used retinas from transgenic mice: Ai148;PVCre and Ai148;PCP2Cre expressing GCaMP6f in RGCs and BCs respectively. Cone photoreceptors expressing S-opsin were targeted for UV pattered and full-field stimulation. A semi-automated algorithm was used to characterize functionally distinct RGCs and BCs based on their spatiotemporal calcium footprints.

Results : The performance of the system was optimized by imaging fluorescent beads and axonal varicosities of individual RGCs. Axial resolution was obtained as ~20-30um, indicating clear laminar separation between the excitation light-sheet and the photoreceptor layer on which the visual stimulus was focused. We routinely imaged somatic activity of 200-300 RGCs (n=5 mice), and ~20-50 BCs (n=2 mice). Using different stimuli, we were able to drive different patterns of calcium activity, that allowed us to classify RGCs into 8-10 types in this mouse line, in agreement with previous anatomical findings. We further imaged visual stimulus evoked calcium activity in the synaptic terminals of multiple BCs simultaneously, and were able to distinguish different BC types from their inter-terminal and intra-terminal activity patterns.

Conclusions : Our platform provides a low-cost high-throughput solution for imaging calcium fluorescence dynamics in large populations of retinal cells at somatic and synaptic resolutions and classifying them based on their response characteristics. These findings have potential implications for revealing how visual signals are transformed at the synapses of functionally distinct BCs and RGCs.

This abstract was presented at the 2022 ARVO Annual Meeting, held in Denver, CO, May 1-4, 2022, and virtually.

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