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Journal Article

Targeting Functionally Characterized Synaptic Architecture Using Inherent Fiducials and 3D Correlative Microscopy

MPS-Authors

Thomas,  Connon I.
Max Planck Florida Institute for Neuroscience, Max Planck Society;

Ryan,  Melissa A.
Max Planck Florida Institute for Neuroscience, Max Planck Society;

Scholl,  Benjamin
Max Planck Florida Institute for Neuroscience, Max Planck Society;

Guerrero-Given,  Debbie
Max Planck Florida Institute for Neuroscience, Max Planck Society;

Fitzpatrick,  David
Max Planck Florida Institute for Neuroscience, Max Planck Society;

Kamasawa,  Naomi
Max Planck Florida Institute for Neuroscience, Max Planck Society;

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Citation

Thomas, C. I., Ryan, M. A., Scholl, B., Guerrero-Given, D., Fitzpatrick, D., & Kamasawa, N. (2020). Targeting Functionally Characterized Synaptic Architecture Using Inherent Fiducials and 3D Correlative Microscopy. Microscopy and Microanalysis, 1-14. Retrieved from https://www.cambridge.org/core/journals/microscopy-and-microanalysis/article/targeting-functionally-characterized-synaptic-architecture-using-inherent-fiducials-and-3d-correlative-microscopy/EE184901AC2D1D0A296829AE6CF8AA3B.


Cite as: https://hdl.handle.net/21.11116/0000-000C-DF8B-D
Abstract
,
Brain circuits are highly interconnected three-dimensional structures fabricated from components ranging vastly in size; from cell bodies to individual synapses. While neuronal activity can be visualized with advanced light microscopy (LM) techniques, the resolution of electron microscopy (EM) is critical for identifying synaptic connections between neurons. Here, we combine these two techniques, affording the advantage of each and allowing for measurements to be made of the same neural features across imaging platforms. We established an EM-label-free workflow utilizing inherent structural features to correlate in vivo two-photon LM and volumetric scanning EM (SEM) in the ferret visual cortex. By optimizing the volume SEM sample preparation protocol, imaging with the OnPoint detector, and utilizing the focal charge compensation device during serial block-face imaging, we achieved sufficient resolution and signal-to-noise ratio to analyze synaptic ultrastructure for hundreds of synapses within sample volumes. Our novel workflow provides a reliable method for quantitatively characterizing synaptic ultrastructure in functionally imaged neurons, providing new insights into neuronal circuit organization.