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 Experiment Video

Updated: Jun 26, 2026

Revealing Neural Circuit Topography in Multi-Color
09:11

Revealing Neural Circuit Topography in Multi-Color

Published on: November 14, 2011

AN OPTIMAL-PATH APPROACH FOR NEURAL CIRCUIT RECONSTRUCTION.

Elizabeth Jurrus1, Ross Whitaker, Bryan W Jones

  • 1School of Computing, University of Utah.

Proceedings. IEEE International Symposium on Biomedical Imaging
|January 28, 2009
PubMed
Summary

Researchers developed an automatic method to find neurons in electron microscopy images. This approach uses Dijkstra's algorithm to trace neuron paths across 2D sections, overcoming manual analysis limitations.

Related Concept Videos

Neural Circuits01:25

Neural Circuits

Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...

You might also read

Related Articles

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

Sort by
Same author

Uncovering the electrical synapse proteome in retinal neurons via in vivo proximity labeling.

eLife·2026
Same author

Impact of Aii Amacrine Cell Rewiring in a Pathoconnectome-Based Computational Model of Early Retinal Degeneration.

bioRxiv : the preprint server for biology·2026
Same author

Self-supervised contrastive learning enables robust electrocardiogram-based cardiac classification.

Heart rhythm O2·2026
Same author

Differential profiles of motor dysfunction in amnestic versus non-amnestic mild cognitive impairment - The Vietnam Era Twin Study of Aging.

Neuroscience·2026
Same author

Predicting Ventricular Arrhythmia in Myocardial Ischemia Using Machine Learning.

Computing in cardiology·2026
Same author

ARD-VAE: A Statistical Formulation to Find the Relevant Latent Dimensions of Variational Autoencoders.

IEEE Winter Conference on Applications of Computer Vision. IEEE Winter Conference on Applications of Computer Vision·2025

Area of Science:

  • Neurobiology
  • Computational Neuroscience
  • Image Analysis

Background:

  • Electron microscopy generates large datasets for studying central nervous system neuron organization.
  • Manual analysis of these large datasets for neural connectivity is impractical.
  • Automated 3D neuron segmentation is challenging due to image complexities.

Purpose of the Study:

  • To describe an automatic method for identifying neurons in sequences of 2D electron microscopy sections.
  • To address the limitations of manual analysis in large-scale neurobiological imaging.
  • To enable efficient extraction of neural connectivity information.

Main Methods:

  • Formulating neuron pathfinding as an optimal path computation problem across image sections.
  • Applying a cost function to identify cells from one section to the next.

More Related Videos

Viral Tracing of Genetically Defined Neural Circuitry
13:06

Viral Tracing of Genetically Defined Neural Circuitry

Published on: October 17, 2012

Related Experiment Videos

Last Updated: Jun 26, 2026

Revealing Neural Circuit Topography in Multi-Color
09:11

Revealing Neural Circuit Topography in Multi-Color

Published on: November 14, 2011

Viral Tracing of Genetically Defined Neural Circuitry
13:06

Viral Tracing of Genetically Defined Neural Circuitry

Published on: October 17, 2012

  • Utilizing Dijkstra's algorithm to solve the optimization problem for pathfinding.

    • Main Results:

    • Successfully developed an automatic method for tracing neurons through 2D sections.
    • The method accounts for variability and inconsistencies between image sections.
    • Prioritizes neuron paths based on connectivity evidence.

    Conclusions:

    • The proposed method offers an efficient and reliable approach for automated neuron tracing.
    • This technique facilitates the analysis of large electron microscopy datasets for neurobiological research.
    • Enables better understanding of neuron organization and connectivity in the central nervous system.