Automated remote focusing, drift correction, and photostimulation to evaluate structural plasticity in dendritic spines

• Type of Material: Article
• Authors: Michael S. Smirnov, Max Planck Florida Institute for Neuroscience; Paul Evans, Emory University; Tavita R. Garrett, Max Planck Florida Institute for Neuroscience; Long Yan, Max Planck Florida Institute for Neuroscience; Ryohei Yasuda, Max Planck Florida Institute for Neuroscience
• Language: English
• Date: 2017-01-01
• Publisher: Public Library of Science
• Publication Version: Final Published Version
• Copyright Statement: © 2017 Smirnov et al.
• License: Creative Commons Attribution 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1371/journal.pone.0170586
• Title of Journal or Parent Work: PLoS ONE
• Volume: 12
• Issue: 1
• Start Page: e0170586
• End Page: e0170586
• Grant/Funding Information: This work was supported by the National Institutes of Health (DP1NS096787 to RY and 1F31NS086174 to PRE) and funding from The Max Planck Florida Institute for Neuroscience and the Max Planck Society.
• Keywords: Graphical user interface; Neuronal dendrites; User interfaces; Neuronal plasticity; Algorithms; Dendritic structure; Synaptic plasticity; Glutamate
• Research Categories: Biology, Neuroscience; Biology, Bioinformatics

Abstract

Long-term structural plasticity of dendritic spines plays a key role in synaptic plasticity, the cellular basis for learning and memory. The biochemical step is mediated by a complex network of signaling proteins in spines. Two-photon imaging techniques combined with twophoton glutamate uncaging allows researchers to induce and quantify structural plasticity in single dendritic spines. However, this method is laborious and slow, making it unsuitable for high throughput screening of factors necessary for structural plasticity. Here we introduce a MATLAB-based module built for Scanimage to automatically track, image, and stimulate multiple dendritic spines. We implemented an electrically tunable lens in combination with a drift correction algorithm to rapidly and continuously track targeted spines and correct sample movements. With a straightforward user interface to design custom multi-position experiments, we were able to adequately image and produce targeted plasticity in multiple dendritic spines using glutamate uncaging. Our methods are inexpensive, open source, and provides up to a five-fold increase in throughput for quantifying structural plasticity of dendritic spines.