Single-Neuron Level One-Photon Voltage Imaging With Sparsely Targeted Genetically Encoded Voltage Indicators
Voltage imaging of many neurons simultaneously at single-cell resolution is hampered by the difficulty of detecting small voltage signals from overlapping neuronal processes in neural tissue. Recent advances in genetically encoded voltage indicator (GEVI) imaging have shown single-cell resolution op...
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Published in | Frontiers in cellular neuroscience Vol. 13; p. 39 |
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Main Authors | , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Switzerland
Frontiers Research Foundation
14.02.2019
Frontiers Media S.A |
Subjects | |
Online Access | Get full text |
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Summary: | Voltage imaging of many neurons simultaneously at single-cell resolution is hampered by the difficulty of detecting small voltage signals from overlapping neuronal processes in neural tissue. Recent advances in genetically encoded voltage indicator (GEVI) imaging have shown single-cell resolution optical voltage recordings in intact tissue through imaging naturally sparse cell classes, sparse viral expression, soma restricted expression, advanced optical systems, or a combination of these. Widespread sparse and strong transgenic GEVI expression would enable straightforward optical access to a densely occurring cell type, such as cortical pyramidal cells. Here we demonstrate that a recently described sparse transgenic expression strategy can enable single-cell resolution voltage imaging of cortical pyramidal cells in intact brain tissue without restricting expression to the soma. We also quantify the functional crosstalk in brain tissue and discuss optimal imaging rates to inform future GEVI experimental design. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Edited by: Josef Bischofberger, Universität Basel, Switzerland Reviewed by: Leonardo Sacconi, Università degli Studi di Firenze, Italy; Markus Rothermel, RWTH Aachen Universität, Germany |
ISSN: | 1662-5102 1662-5102 |
DOI: | 10.3389/fncel.2019.00039 |