Abstract
Neurons are the main cellular components of the circuits of the central nervous system (CNS). The dendritic and axonal morphology of individual neurons display marked variability between neurons in different regions of the CNS, and there is evidence that the morphology of a neuron has a strong impact on its function. For studies of structure-function relationships of specific types of neurons, it is important to visualize and quantify the complete neuronal morphology. In addition, realistic and detailed morphological reconstruction is essential for developing compartmental models that can be used for studying neuronal computation and signal processing. Here we describe in detail how multiphoton excitation (MPE) microscopy of dye-filled neurons can be used for visualization and imaging of neuronal morphology, followed by a workflow with digital deconvolution and manual or semiautomatic morphological reconstruction. The specific advantages of MPE structural imaging are low phototoxicity, the ease with which it can be combined with parallel physiological measurements from the same neurons, and the elimination of tissue post-processing and fixation-related artifacts. Because manual morphological reconstruction can be very time-consuming, this chapter also includes a detailed, step-by-step description of a workflow for semiautomatic morphological reconstruction (using freely available software developed in our laboratory), exemplified by reconstruction of a retinal amacrine cell (AII).
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Acknowledgments
This research was supported by The Research Council of Norway (NFR 182743, 189662, 214216 to EH; NFR 213776, 261914 to MLV).
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Appendix A: Recommended Parameter Values for Automated Reconstruction
Appendix A: Recommended Parameter Values for Automated Reconstruction
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Hartveit, E., Zandt, BJ., Veruki, M.L. (2019). Multiphoton Excitation Microscopy for the Reconstruction and Analysis of Single Neuron Morphology. In: Hartveit, E. (eds) Multiphoton Microscopy. Neuromethods, vol 148. Humana, New York, NY. https://doi.org/10.1007/978-1-4939-9702-2_8
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DOI: https://doi.org/10.1007/978-1-4939-9702-2_8
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