4.4 Article

Automated analysis of neuronal morphology, synapse number and synaptic recruitment

期刊

JOURNAL OF NEUROSCIENCE METHODS
卷 195, 期 2, 页码 185-193

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.jneumeth.2010.12.011

关键词

Neuronal morphology; Immuno-fluorescence; Synapses; Dendrites; Image analysis; Synaptopathies

资金

  1. Neuromics Marie Curie Early stage Training grant [MEST-CT-2005-020919]
  2. Netherlands Scientific Organization [NWO 021.001.076]
  3. NWO [635.100.017]

向作者/读者索取更多资源

The shape, structure and connectivity of nerve cells are important aspects of neuronal function. Genetic and epigenetic factors that alter neuronal morphology or synaptic localization of pre- and post-synaptic proteins contribute significantly to neuronal output and may underlie clinical states. To assess the impact of individual genes and disease-causing mutations on neuronal morphology, reliable methods are needed. Unfortunately, manual analysis of immuno-fluorescence images of neurons to quantify neuronal shape and synapse number, size and distribution is labor-intensive, time-consuming and subject to human bias and error. We have developed an automated image analysis routine using steerable filters and deconvolutions to automatically analyze dendrite and synapse characteristics in immuno-fluorescence images. Our approach reports dendrite morphology, synapse size and number but also synaptic vesicle density and synaptic accumulation of proteins as a function of distance from the soma as consistent as expert observers while reducing analysis time considerably. In addition, the routine can be used to detect and quantify a wide range of neuronal organelles and is capable of batch analysis of a large number of images enabling high-throughput analysis. (C) 2010 Elsevier B.V. All rights reserved.

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