Computational geometry analysis of dendritic spines by structured illumination microscopy View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-12

AUTHORS

Yutaro Kashiwagi, Takahito Higashi, Kazuki Obashi, Yuka Sato, Noboru H. Komiyama, Seth G. N. Grant, Shigeo Okabe

ABSTRACT

Dendritic spines are the postsynaptic sites that receive most of the excitatory synaptic inputs, and thus provide the structural basis for synaptic function. Here, we describe an accurate method for measurement and analysis of spine morphology based on structured illumination microscopy (SIM) and computational geometry in cultured neurons. Surface mesh data converted from SIM images were comparable to data reconstructed from electron microscopic images. Dimensional reduction and machine learning applied to large data sets enabled identification of spine phenotypes caused by genetic mutations in key signal transduction molecules. This method, combined with time-lapse live imaging and glutamate uncaging, could detect plasticity-related changes in spine head curvature. The results suggested that the concave surfaces of spines are important for the long-term structural stabilization of spines by synaptic adhesion molecules. More... »

PAGES

1285

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/s41467-019-09337-0

    DOI

    http://dx.doi.org/10.1038/s41467-019-09337-0

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1112870977

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/30894537


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