Abstract

Two-photon microscopy is used to image neuronal activity, but has severe limitations for studying deeper cortical layers. Here, we developed a custom three-photon microscope optimized to image a vertical column of the cerebral cortex > 1 mm in depth in awake mice with low (<20 mW) average laser power. Our measurements of physiological responses and tissue-damage thresholds define pulse parameters and safety limits for damage-free three-photon imaging. We image functional visual responses of neurons expressing GCaMP6s across all layers of the primary visual cortex (V1) and in the subplate. These recordings reveal diverse visual selectivity in deep layers: layer 5 neurons are more broadly tuned to visual stimuli, whereas mean orientation selectivity of layer 6 neurons is slightly sharper, compared to neurons in other layers. Subplate neurons, located in the white matter below cortical layer 6 and characterized here for the first time, show low visual responsivity and broad orientation selectivity.

Two-photon microscopy is a powerful tool for studying neuronal activity but cannot easily image deeper cortical layers. Here, the authors design a custom microscope for three-photon microscopy and use it to reveal response properties of layer 5, 6, and subplate visual cortical neurons.

Details

Title
Functional imaging of visual cortical layers and subplate in awake mice with optimized three-photon microscopy
Author
Yildirim Murat 1   VIAFID ORCID Logo  ; Sugihara Hiroki 2   VIAFID ORCID Logo  ; So, Peter T, C 3 ; Sur Mriganka 4   VIAFID ORCID Logo 

 Massachusetts Institute of Technology, Picower Institute for Learning and Memory, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786) ; Massachusetts Institute of Technology, Department of Biological Engineering, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786) 
 Massachusetts Institute of Technology, Picower Institute for Learning and Memory, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786) 
 Massachusetts Institute of Technology, Department of Biological Engineering, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786) ; Massachusetts Institute of Technology, Department of Mechanical Engineering, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786) 
 Massachusetts Institute of Technology, Picower Institute for Learning and Memory, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786) ; Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences, Cambridge, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786) 
Publication year
2019
Publication date
Jan 2019
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
1922175081
Copyright
This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.