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

Propagation of Action Potentials01:23

Propagation of Action Potentials

8.5K
The propagation of an action potential refers to the process by which a nerve impulse, or "action potential," travels along a neuron.
Neurons (nerve cells) have a resting membrane potential, with a slightly negative charge inside compared to outside. This is maintained by ion channels, such as sodium (Na+) and potassium (K+) channels, which control the flow of ions. When a stimulus, like a touch or a signal from another neuron, triggers the neuron, sodium channels open, allowing sodium ions to...
8.5K
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

6.8K
Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
6.8K
Neural Circuits01:25

Neural Circuits

2.5K
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...
2.5K
Classification of Neurotransmitters01:30

Classification of Neurotransmitters

4.8K
Neurotransmitters play a crucial role in the communication between neurons in the autonomic nervous system. Neurons in the autonomic nervous system can be cholinergic or adrenergic depending on the neurotransmitters synthesized. Cholinergic neurons use acetylcholine as their primary neurotransmitter. This includes all the preganglionic fibers of the sympathetic and pre- and postganglionic fibers of the parasympathetic nervous systems. In addition, neurons of the somatic nervous system also use...
4.8K
Neuron Structure01:31

Neuron Structure

230.1K
Overview
230.1K
Neuron Structure01:30

Neuron Structure

17.4K
Neurons are the main type of cell in the nervous system that generate and transmit electrochemical signals. They primarily communicate with each other using neurotransmitters at specific junctions called synapses. Neurons come in many shapes that often relate to their function, but most share three main structures: an axon and dendrites that extend out from a cell body.
Structure and Function of Neurons
The neuronal cell body—the soma— houses the nucleus and organelles vital to...
17.4K

You might also read

Related Articles

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

Sort by
Same author

Does fly larval cooperative behavior protect against parasitic wasps?

Journal of comparative physiology. A, Neuroethology, sensory, neural, and behavioral physiology·2026
Same author

Deep Temporal Sequence Classification and Mathematical Modeling for Cell Tracking in Dense 3D Microscopy Videos of Bacterial Biofilms.

IEEE transactions on computational biology and bioinformatics·2026
Same author

Do wild-caught fly larvae cooperatively forage?

Journal of comparative physiology. A, Neuroethology, sensory, neural, and behavioral physiology·2024
Same author

DeepSeeded: Volumetric Segmentation of Dense Cell Populations with a Cascade of Deep Neural Networks in Bacterial Biofilm Applications.

Expert systems with applications·2024
Same author

Population parameters of Drosophila larval cooperative foraging.

Journal of comparative physiology. A, Neuroethology, sensory, neural, and behavioral physiology·2024
Same author

A Semantic and Motion-Aware Spatiotemporal Transformer Network for Action Detection.

IEEE transactions on pattern analysis and machine intelligence·2024
Same journal

Metabolically Faithful 3D PET Restoration via Volumetric Swin Transformers.

Neuroinformatics·2026
Same journal

CytoCLIP: Learning Cytoarchitectural Characteristics in Developing Human Brain Using Contrastive Language Image Pre-Training.

Neuroinformatics·2026
Same journal

Increasing the Reliability of Functional Connectivity by Predicting Long-Scan Functional Connectivity based on Short-Scan Functional Connectivity: Model Exploration, Explanation, Validation, and Application.

Neuroinformatics·2026
Same journal

HESREN: A Derivative-Informed Reservoir Framework for Detecting Transient Neural Events and Windowless Estimation of Dynamic Functional Connectivity.

Neuroinformatics·2026
Same journal

Computational Morphometry of Peripheral Nerves: A Pipeline Perspective on Reproducibility and Generalization.

Neuroinformatics·2026
Same journal

Multimodal Branched Transport Infers Anatomically Aligned Brain Reaction Maps.

Neuroinformatics·2026
See all related articles

Related Experiment Video

Updated: Dec 27, 2025

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

7.3K

NeuroPath2Path: Classification and elastic morphing between neuronal arbors using path-wise similarity.

Tamal Batabyal1, Barry Condron2, Scott T Acton3,4

  • 1Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, VA, USA. tb2ea@virginia.edu.

Neuroinformatics
|February 29, 2020
PubMed
Summary
This summary is machine-generated.

We introduce NeuroPath2Path (NeuroP2P), a novel graph-theoretic method for analyzing neuron morphology. This approach effectively measures neuronal distance by continuously morphing path sets, outperforming existing techniques.

Keywords:
Assignment algorithmBiomedical image analysisElastic morphingNeuron morphologyShape classificationTree matching

More Related Videos

Automatic Identification of Dendritic Branches and their Orientation
06:08

Automatic Identification of Dendritic Branches and their Orientation

Published on: September 17, 2021

2.2K
Morphological Analysis of Drosophila Larval Peripheral Sensory Neuron Dendrites and Axons Using Genetic Mosaics
09:42

Morphological Analysis of Drosophila Larval Peripheral Sensory Neuron Dendrites and Axons Using Genetic Mosaics

Published on: November 7, 2011

15.7K

Related Experiment Videos

Last Updated: Dec 27, 2025

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

7.3K
Automatic Identification of Dendritic Branches and their Orientation
06:08

Automatic Identification of Dendritic Branches and their Orientation

Published on: September 17, 2021

2.2K
Morphological Analysis of Drosophila Larval Peripheral Sensory Neuron Dendrites and Axons Using Genetic Mosaics
09:42

Morphological Analysis of Drosophila Larval Peripheral Sensory Neuron Dendrites and Axons Using Genetic Mosaics

Published on: November 7, 2011

15.7K

Area of Science:

  • Computational Neuroscience
  • Graph Theory Applications
  • Neuroinformatics

Background:

  • Neuron morphology significantly influences brain function.
  • Extracting detailed morphological information is crucial for understanding neural circuits.
  • Graph theory offers a powerful framework for analyzing complex neuronal structures.

Purpose of the Study:

  • To develop an efficacious graph-theoretic method for analyzing neuronal morphology.
  • To address challenges in subgraph matching and temporal shape analysis.
  • To quantify neuronal shape differences using a novel morphing approach.

Main Methods:

  • Proposed a model based on rooted path decomposition from soma to dendrites.
  • Extracted morphological features from constituent paths.
  • Utilized a modified Munkres algorithm for path correspondence.
  • Employed an elastic deformation framework with square root velocity functions for continuous morphing.

Main Results:

  • Established a novel method, NeuroPath2Path (NeuroP2P), for neuronal morphology analysis.
  • Demonstrated the efficacy of continuous morphing for measuring neuronal distance.
  • Showcased NeuroP2P's superior performance compared to state-of-the-art methods.
  • Provided an effective visualization tool through the elastic deformation framework.

Conclusions:

  • NeuroPath2Path offers a robust and effective solution for analyzing complex neuronal morphology.
  • The method successfully quantifies neuronal shape differences and facilitates comparative analysis.
  • This approach advances the application of graph theory in computational neuroscience.