August 2019
Volume 60, Issue 11
Open Access
ARVO Imaging in the Eye Conference Abstract  |   August 2019
Characterizing spatial distribution of neuronal cell types in visual areas of mice brain imaged using Serial 2-photon tomography
Author Affiliations & Notes
  • Kannan U V
    Neuroscience, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States
  • Ramesh Palaniswamy
    Neuroscience, Cold Spring Harbor Laboratory, Floral Park, New York, United States
  • Nicholas Cain
    Allen Institute for Brain Sciences, Seattle, Washington, United States
  • Julie Harris
    Allen Institute for Brain Sciences, Seattle, Washington, United States
  • Pavel Osten
    Neuroscience, Cold Spring Harbor Laboratory, Floral Park, New York, United States
  • Footnotes
    Commercial Relationships   Kannan U V, None; Ramesh Palaniswamy, None; Nicholas Cain, None; Julie Harris, None; Pavel Osten, None
  • Footnotes
    Support  NIH R01MH096946, U01MH105971
Investigative Ophthalmology & Visual Science August 2019, Vol.60, PB0187. doi:
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      Kannan U V, Ramesh Palaniswamy, Nicholas Cain, Julie Harris, Pavel Osten; Characterizing spatial distribution of neuronal cell types in visual areas of mice brain imaged using Serial 2-photon tomography. Invest. Ophthalmol. Vis. Sci. 2019;60(11):PB0187.

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

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Abstract

Purpose : Many molecularly defined neuronal types have been discovered in last few decades. We don’t have a comprehensive understanding on the distribution of these cell types in the whole brain, different functional pathways and within each region of these pathways. These series of experiments help in mapping the distribution of few of these cell types in different regions involved in the visual pathway of the mouse brain.

Methods : Novel mice created from Allen Institute of Brain Study’s library of molecularly defined cell types have these different cell types fluorescently labeled. 5 male and 5 female 8-10-week-old mice are killed and perfused and embedded in an agarose block and crosslinked. Once fixed these brains are imaged using a serial two-photon tomography (STPT) microscope. The entire brains are imaged in multiple field of views of 800mx800m at 1m x 1m XY resolution. Each coronal section is imaged with 16x12 FOVs with 10% overlap and spaced 50m apart in Z. All the FOVs are stitched together to create a whole mouse brain image of size 13000x9000x280 voxels. The fluorescently labeled cells are automatically identified using a convolution neural network (CNN) across the whole brain. The CNN was trained using markups from 60 FOV randomly sampled from different regions across the entire brain. Further, the sample brains are registered to the Allen Brain Institute’s Common co-ordinate framework (CCF) space. The cell densities are computed for all the cell types in the CCF space. The cell density maps of the visual areas are extracted and clustered to identify the similarity in distribution.

Results : We have characterized the cell distribution maps multiple cell types in the following areas of the visual pathway:
Anterolateral visual area (VISal)
Anteromedial visual area (VISam)
Lateral visual area (VISl)
Primary visual area (VISp)
Posterolateral visual area (VISpl)
posteromedial visual area (VISpm)
Lateral geniculate nucleus (LGN)

For the following cell types:
Parvalbumin
Slc32
Gad2
Chat
Ctgf-T2A
Rbp4
Rorb
Cux2
Nstr1
Tlx3
Emx1

Conclusions : This work has generated density maps of various cell types in regions of the brain involved in the visual system. These cell types have been clustered based on the spatial distribution of the cells.

This abstract was presented at the 2019 ARVO Imaging in the Eye Conference, held in Vancouver, Canada, April 26-27, 2019.

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