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Automatic Dendritic Spine Quantification from Confocal Data with Neurolucida 360.
Dickstein, Dara L; Dickstein, Daniel R; Janssen, William G M; Hof, Patrick R; Glaser, Jacob R; Rodriguez, Alfredo; O'Connor, Nate; Angstman, Paul; Tappan, Susan J.
Afiliação
  • Dickstein DL; Fishberg Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York.
  • Dickstein DR; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York.
  • Janssen WGM; Computational Neurobiology and Imaging Center, Icahn School of Medicine at Mount Sinai, New York, New York.
  • Hof PR; Fishberg Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York.
  • Glaser JR; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York.
  • Rodriguez A; Fishberg Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York.
  • O'Connor N; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York.
  • Angstman P; Fishberg Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York.
  • Tappan SJ; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York.
Curr Protoc Neurosci ; 77: 1.27.1-1.27.21, 2016 10 03.
Article em En | MEDLINE | ID: mdl-27696360
ABSTRACT
Determining the density and morphology of dendritic spines is of high biological significance given the role of spines in synaptic plasticity and in neurodegenerative and neuropsychiatric disorders. Precise quantification of spines in three dimensions (3D) is essential for understanding the structural determinants of normal and pathological neuronal function. However, this quantification has been restricted to time- and labor-intensive methods such as electron microscopy and manual counting, which have limited throughput and are impractical for studies of large samples. While there have been some automated software packages that quantify spine number, they are limited in terms of their characterization of spine structure. This unit presents methods for objective dendritic spine morphometric analysis by providing image acquisition parameters needed to ensure optimal data series for proper spine detection, characterization, and quantification with Neurolucida 360. These protocols will be a valuable reference for scientists working towards quantifying and characterizing spines. © 2016 by John Wiley & Sons, Inc.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Microscopia Confocal / Imageamento Tridimensional / Espinhas Dendríticas / Plasticidade Neuronal / Neurônios Limite: Animals Idioma: En Revista: Curr Protoc Neurosci Ano de publicação: 2016 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Microscopia Confocal / Imageamento Tridimensional / Espinhas Dendríticas / Plasticidade Neuronal / Neurônios Limite: Animals Idioma: En Revista: Curr Protoc Neurosci Ano de publicação: 2016 Tipo de documento: Article