Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Loss of all three APP family members during development impairs synaptic function and plasticity, disrupts learning, and causes an autism-like phenotype.

The EMBO journal·2021
See all related articles

Related Experiment Video

Updated: Dec 15, 2025

Semi-Quantitative Determination of Dopaminergic Neuron Density in the Substantia Nigra of Rodent Models using Automated Image Analysis
06:09

Semi-Quantitative Determination of Dopaminergic Neuron Density in the Substantia Nigra of Rodent Models using Automated Image Analysis

Published on: February 2, 2021

4.9K

Basic quantitative morphological methods applied to the central nervous system.

Lutz Slomianka1

  • 1University of Zürich, Institute of Anatomy, Zürich, Switzerland.

The Journal of Comparative Neurology
|July 9, 2020
PubMed
Summary

Design-based stereology offers reliable methods for quantifying nervous system structures like volume and length. These techniques ensure accurate, reproducible numerical data for research, overcoming common methodological challenges.

Keywords:
design-based stereologylengthnumberquantitative morphologysurfacevolume

More Related Videos

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
12:27

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

7.2K
Quantitative Approaches for Studying Cellular Structures and Organelle Morphology in Caenorhabditis elegans
08:47

Quantitative Approaches for Studying Cellular Structures and Organelle Morphology in Caenorhabditis elegans

Published on: July 5, 2019

10.2K

Related Experiment Videos

Last Updated: Dec 15, 2025

Semi-Quantitative Determination of Dopaminergic Neuron Density in the Substantia Nigra of Rodent Models using Automated Image Analysis
06:09

Semi-Quantitative Determination of Dopaminergic Neuron Density in the Substantia Nigra of Rodent Models using Automated Image Analysis

Published on: February 2, 2021

4.9K
Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
12:27

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

7.2K
Quantitative Approaches for Studying Cellular Structures and Organelle Morphology in Caenorhabditis elegans
08:47

Quantitative Approaches for Studying Cellular Structures and Organelle Morphology in Caenorhabditis elegans

Published on: July 5, 2019

10.2K

Area of Science:

  • Neuroscience
  • Quantitative Biology
  • Stereology

Background:

  • Accurate numerical data is crucial for objective analysis in neuroscience.
  • Traditional methods often fail to meet the demands for clarity and statistical validity.
  • Quantifying neural structures requires robust and reproducible techniques.

Purpose of the Study:

  • To review challenges in generating quantitative data for nervous system morphology.
  • To provide accessible descriptions of design-based stereology methods.
  • To emphasize the practical application of stereology for neuroscience research.

Main Methods:

  • Design-based stereology principles are explained.
  • Focus on estimators for volume, surface, length, and number of neural components.
  • Integration of sampling strategies with stereological probes for efficient assessment.

Main Results:

  • Design-based stereology provides mathematically sound and reliable quantitative data.
  • Understanding the mathematical background is not essential for practical application.
  • Methods faithfully reflect histological material properties and anatomical considerations.

Conclusions:

  • Stereological methods enable the generation of valid and practically useful numerical data for neuroscience.
  • These methods can reduce discrepancies in experimental results.
  • Integrating quantitative data with qualitative knowledge is key to understanding neural function.