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      Three dimensional two-photon brain imaging in freely moving mice using a miniature fiber coupled microscope with active axial-scanning

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          Abstract

          We present a miniature head mounted two-photon fiber-coupled microscope (2P-FCM) for neuronal imaging with active axial focusing enabled using a miniature electrowetting lens. We show three-dimensional two-photon imaging of neuronal structure and record neuronal activity from GCaMP6s fluorescence from multiple focal planes in a freely-moving mouse. Two-color simultaneous imaging of GFP and tdTomato fluorescence is also demonstrated. Additionally, dynamic control of the axial scanning of the electrowetting lens allows tilting of the focal plane enabling neurons in multiple depths to be imaged in a single plane. Two-photon imaging allows increased penetration depth in tissue yielding a working distance of 450 μm with an additional 180 μm of active axial focusing. The objective NA is 0.45 with a lateral resolution of 1.8 μm, an axial resolution of 10 μm, and a field-of-view of 240 μm diameter. The 2P-FCM has a weight of only ~2.5 g and is capable of repeatable and stable head-attachment. The 2P-FCM with dynamic axial scanning provides a new capability to record from functionally distinct neuronal layers, opening new opportunities in neuroscience research.

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          Most cited references51

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          Two-photon laser scanning fluorescence microscopy

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            Long-term dynamics of CA1 hippocampal place codes

            Via Ca2+-imaging in freely behaving mice that repeatedly explored a familiar environment, we tracked thousands of CA1 pyramidal cells' place fields over weeks. Place coding was dynamic, for each day the ensemble representation of this environment involved a unique subset of cells. Yet, cells within the ∼15–25% overlap between any two of these subsets retained the same place fields, which sufficed to preserve an accurate spatial representation across weeks.
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              Tests to assess motor phenotype in mice: a user's guide.

              The characterization of mouse models of human disease is essential for understanding the underlying pathophysiology and developing new therapeutics. Many diseases are often associated with more than one model, and so there is a need to determine which model most closely represents the disease state or is most suited to the therapeutic approach under investigation. In the case of neurological disease, motor tests provide a good read-out of neurological function. This overview of available motor tasks aims to aid researchers in making the correct choice of test when attempting to tease out a transgenic phenotype or when assessing the recovery of motor function following therapeutic intervention.
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                Author and article information

                Contributors
                Baris.Ozbay@ucdenver.edu
                Diego.Restrepo@ucdenver.edu
                Emily.Gibson@ucdenver.edu
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                25 May 2018
                25 May 2018
                2018
                : 8
                : 8108
                Affiliations
                [1 ]ISNI 0000 0001 0703 675X, GRID grid.430503.1, Department of Bioengineering, , University of Colorado Denver, Anschutz Medical Campus, ; Aurora, CO 80045 USA
                [2 ]ISNI 0000 0001 0703 675X, GRID grid.430503.1, Department of Cell & Developmental Biology, , University of Colorado Denver, Anschutz Medical Campus, ; Aurora, CO 80045 USA
                [3 ]ISNI 0000 0001 0703 675X, GRID grid.430503.1, Neuroscience Program, , University of Colorado Denver, Anschutz Medical Campus, ; Aurora, CO 80045 USA
                [4 ]ISNI 0000000096214564, GRID grid.266190.a, Department of Mechanical Engineering, , University of Colorado Boulder, ; Colorado, 80309 USA
                [5 ]ISNI 0000000096214564, GRID grid.266190.a, Department of Electrical, Computer and Energy Engineering, , University of Colorado Boulder, ; Colorado, 80309 USA
                Author information
                http://orcid.org/0000-0002-2694-577X
                http://orcid.org/0000-0003-2266-9525
                http://orcid.org/0000-0003-3243-7429
                http://orcid.org/0000-0002-3436-1483
                Article
                26326
                10.1038/s41598-018-26326-3
                5970169
                29802371
                32f79024-4032-4a6f-90d0-cc03fa44671a
                © The Author(s) 2018

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 9 October 2017
                : 9 May 2018
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