Format

Send to

Choose Destination
Curr Protoc Neurosci. 2016 Oct 3;77:1.27.1-1.27.21. doi: 10.1002/cpns.16.

Automatic Dendritic Spine Quantification from Confocal Data with Neurolucida 360.

Author information

1
Fishberg Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York.
2
Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York.
3
Computational Neurobiology and Imaging Center, Icahn School of Medicine at Mount Sinai, New York, New York.
4
MBF Bioscience, Williston, Vermont.

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.

KEYWORDS:

automated quantification; confocal microscopy; dendritic spines; neurons

PMID:
27696360
PMCID:
PMC5113738
DOI:
10.1002/cpns.16
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Wiley Icon for PubMed Central
Loading ...
Support Center