Computing neurite outgrowth and arborization in superior cervical ganglion neurons

Rachel Henley, Vidya Chandrasekaran, Cecilia R Giulivi

Research output: Contribution to journalArticle

Abstract

Dendrites are the primary site of synaptic activity in neurons and changes in synapses are often the first pathological stage in neurodegenerative diseases. Molecular studies of these changes rely on morphological analysis of the imaging of somas and dendritic arbors of cultured or primary neurons. As research on preventing or reversing synaptic degeneration develops, demands increase for user-friendly 2D neurite analyzers without undermining accuracy and reproducibility. The most common method of 2D neurite analysis is manual by using ImageJ. This method relies completely on the user's ability to distinguish the shape and size of dendrites and trace morphology with a series of straight connected lines. Semi-automatic methods have also been developed, such as the NeuronJ plugin for ImageJ. These methods still rely on the user to identify the start and end of the dendrites, but automatically determine the shape, reducing the likelihood of user bias and speeding the process. Some automatic methods have been developed through image processing software, like ImagePro. These programs tend to be expensive, but have been shown to be fast and effective, limiting user interaction. In this study, we compare three methods of neurite analysis—ImageJ, NeuronJ, and ImagePro—in measuring the soma size, number of dendrites, and length of dendrites per cell of embryonic sympathetic rat neurons with BMP-7-induced dendritic growth. Our results indicate that ImageJ and NeuronJ measurements were of similar effectiveness and consistent throughout various images and multiple trials. NeuronJ required less user interaction in measuring the length of dendrites than the manual method and therefore, was faster and less labor intensive. Conversely, ImagePro tended to be inconsistent across images, overestimating both soma size and the number of dendrites per cell while underestimating the length of dendrites. Overall, NeuronJ, in conjunction with ImageJ, is the most reliable and efficient method of 2D neurite analysis tested in the present study.

LanguageEnglish (US)
Pages194-199
Number of pages6
JournalBrain Research Bulletin
Volume144
DOIs
StatePublished - Jan 1 2019

Fingerprint

Superior Cervical Ganglion
Dendrites
Neurons
Neurites
Carisoprodol
Bone Morphogenetic Protein 7
Neuronal Outgrowth
Neurodegenerative Diseases
Synapses
Software
Growth

Keywords

  • Automatic neurite tracing
  • Dendritic growth
  • Fluorescent microscopy
  • Method validation
  • Neurite tracing
  • Sympathetic neurons

ASJC Scopus subject areas

  • Neuroscience(all)

Cite this

Computing neurite outgrowth and arborization in superior cervical ganglion neurons. / Henley, Rachel; Chandrasekaran, Vidya; Giulivi, Cecilia R.

In: Brain Research Bulletin, Vol. 144, 01.01.2019, p. 194-199.

Research output: Contribution to journalArticle

@article{2cbf1ce5aa684ef8961df984fb798070,
title = "Computing neurite outgrowth and arborization in superior cervical ganglion neurons",
abstract = "Dendrites are the primary site of synaptic activity in neurons and changes in synapses are often the first pathological stage in neurodegenerative diseases. Molecular studies of these changes rely on morphological analysis of the imaging of somas and dendritic arbors of cultured or primary neurons. As research on preventing or reversing synaptic degeneration develops, demands increase for user-friendly 2D neurite analyzers without undermining accuracy and reproducibility. The most common method of 2D neurite analysis is manual by using ImageJ. This method relies completely on the user's ability to distinguish the shape and size of dendrites and trace morphology with a series of straight connected lines. Semi-automatic methods have also been developed, such as the NeuronJ plugin for ImageJ. These methods still rely on the user to identify the start and end of the dendrites, but automatically determine the shape, reducing the likelihood of user bias and speeding the process. Some automatic methods have been developed through image processing software, like ImagePro. These programs tend to be expensive, but have been shown to be fast and effective, limiting user interaction. In this study, we compare three methods of neurite analysis—ImageJ, NeuronJ, and ImagePro—in measuring the soma size, number of dendrites, and length of dendrites per cell of embryonic sympathetic rat neurons with BMP-7-induced dendritic growth. Our results indicate that ImageJ and NeuronJ measurements were of similar effectiveness and consistent throughout various images and multiple trials. NeuronJ required less user interaction in measuring the length of dendrites than the manual method and therefore, was faster and less labor intensive. Conversely, ImagePro tended to be inconsistent across images, overestimating both soma size and the number of dendrites per cell while underestimating the length of dendrites. Overall, NeuronJ, in conjunction with ImageJ, is the most reliable and efficient method of 2D neurite analysis tested in the present study.",
keywords = "Automatic neurite tracing, Dendritic growth, Fluorescent microscopy, Method validation, Neurite tracing, Sympathetic neurons",
author = "Rachel Henley and Vidya Chandrasekaran and Giulivi, {Cecilia R}",
year = "2019",
month = "1",
day = "1",
doi = "10.1016/j.brainresbull.2018.12.001",
language = "English (US)",
volume = "144",
pages = "194--199",
journal = "Brain Research Bulletin",
issn = "0361-9230",
publisher = "Elsevier Inc.",

}

TY - JOUR

T1 - Computing neurite outgrowth and arborization in superior cervical ganglion neurons

AU - Henley, Rachel

AU - Chandrasekaran, Vidya

AU - Giulivi, Cecilia R

PY - 2019/1/1

Y1 - 2019/1/1

N2 - Dendrites are the primary site of synaptic activity in neurons and changes in synapses are often the first pathological stage in neurodegenerative diseases. Molecular studies of these changes rely on morphological analysis of the imaging of somas and dendritic arbors of cultured or primary neurons. As research on preventing or reversing synaptic degeneration develops, demands increase for user-friendly 2D neurite analyzers without undermining accuracy and reproducibility. The most common method of 2D neurite analysis is manual by using ImageJ. This method relies completely on the user's ability to distinguish the shape and size of dendrites and trace morphology with a series of straight connected lines. Semi-automatic methods have also been developed, such as the NeuronJ plugin for ImageJ. These methods still rely on the user to identify the start and end of the dendrites, but automatically determine the shape, reducing the likelihood of user bias and speeding the process. Some automatic methods have been developed through image processing software, like ImagePro. These programs tend to be expensive, but have been shown to be fast and effective, limiting user interaction. In this study, we compare three methods of neurite analysis—ImageJ, NeuronJ, and ImagePro—in measuring the soma size, number of dendrites, and length of dendrites per cell of embryonic sympathetic rat neurons with BMP-7-induced dendritic growth. Our results indicate that ImageJ and NeuronJ measurements were of similar effectiveness and consistent throughout various images and multiple trials. NeuronJ required less user interaction in measuring the length of dendrites than the manual method and therefore, was faster and less labor intensive. Conversely, ImagePro tended to be inconsistent across images, overestimating both soma size and the number of dendrites per cell while underestimating the length of dendrites. Overall, NeuronJ, in conjunction with ImageJ, is the most reliable and efficient method of 2D neurite analysis tested in the present study.

AB - Dendrites are the primary site of synaptic activity in neurons and changes in synapses are often the first pathological stage in neurodegenerative diseases. Molecular studies of these changes rely on morphological analysis of the imaging of somas and dendritic arbors of cultured or primary neurons. As research on preventing or reversing synaptic degeneration develops, demands increase for user-friendly 2D neurite analyzers without undermining accuracy and reproducibility. The most common method of 2D neurite analysis is manual by using ImageJ. This method relies completely on the user's ability to distinguish the shape and size of dendrites and trace morphology with a series of straight connected lines. Semi-automatic methods have also been developed, such as the NeuronJ plugin for ImageJ. These methods still rely on the user to identify the start and end of the dendrites, but automatically determine the shape, reducing the likelihood of user bias and speeding the process. Some automatic methods have been developed through image processing software, like ImagePro. These programs tend to be expensive, but have been shown to be fast and effective, limiting user interaction. In this study, we compare three methods of neurite analysis—ImageJ, NeuronJ, and ImagePro—in measuring the soma size, number of dendrites, and length of dendrites per cell of embryonic sympathetic rat neurons with BMP-7-induced dendritic growth. Our results indicate that ImageJ and NeuronJ measurements were of similar effectiveness and consistent throughout various images and multiple trials. NeuronJ required less user interaction in measuring the length of dendrites than the manual method and therefore, was faster and less labor intensive. Conversely, ImagePro tended to be inconsistent across images, overestimating both soma size and the number of dendrites per cell while underestimating the length of dendrites. Overall, NeuronJ, in conjunction with ImageJ, is the most reliable and efficient method of 2D neurite analysis tested in the present study.

KW - Automatic neurite tracing

KW - Dendritic growth

KW - Fluorescent microscopy

KW - Method validation

KW - Neurite tracing

KW - Sympathetic neurons

UR - http://www.scopus.com/inward/record.url?scp=85058149618&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85058149618&partnerID=8YFLogxK

U2 - 10.1016/j.brainresbull.2018.12.001

DO - 10.1016/j.brainresbull.2018.12.001

M3 - Article

VL - 144

SP - 194

EP - 199

JO - Brain Research Bulletin

T2 - Brain Research Bulletin

JF - Brain Research Bulletin

SN - 0361-9230

ER -