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

Neurochemical Transmission: Sites of Drug Action01:26

Neurochemical Transmission: Sites of Drug Action

2.3K
Neurochemical transmission, the conduction of electrical impulses between neurons mediated by neurotransmitters, plays a vital role in various physiological processes. Autonomic drugs exert their effects by modulating neurotransmission within the autonomic nervous system. For instance, drugs such as hemicholinium block the precursor uptake necessary for synthesizing acetylcholine, an essential autonomic neurotransmitter. Following synthesis, neurotransmitters are stored in vesicles. Metyrosine...
2.3K
Chemical Synapses01:26

Chemical Synapses

8.8K
Chemical synapses are specialized sites between two neurons or between a neuron and a non-neuronal cell like a muscle, glandular or sensory cell.
Because chemical synapses depend on the release of neurotransmitter molecules from synaptic vesicles to pass on their signal, there is an approximately one millisecond delay between when the axon potential reaches the presynaptic terminal and when the neurotransmitter leads to opening of postsynaptic ion channels. Additionally, this signaling is...
8.8K
Excitatory and Inhibitory Effects of Neurotransmitters01:29

Excitatory and Inhibitory Effects of Neurotransmitters

10.0K
When an action potential reaches the presynaptic axon terminal, it releases neurotransmitters from the neuron into the synaptic cleft at a chemical synapse. The released neurotransmitter can be excitatory or inhibitory. The critical criteria commonly used to determine whether a molecule is a neurotransmitter at a chemical synapse are the molecule's presence in the presynaptic neuron. Second, its release is in response to strong presynaptic depolarization. And lastly, the presence of...
10.0K
Action Potential01:31

Action Potential

8.0K
Neurons communicate by firing action potentials—the electrochemical signal that is propagated along the axon. The signal results in the release of neurotransmitters at axon terminals, thereby transmitting information to the nervous system. An action potential is a specific "all-or-none" change in membrane potential that results in a rapid spike in voltage.
Membrane potential in neurons
Neurons typically have a resting membrane potential of about -70 millivolts (mV). When they...
8.0K
Electrochemical Gradient and Channel Proteins: An Overview01:21

Electrochemical Gradient and Channel Proteins: An Overview

2.3K
An electrochemical gradient is a fundamental concept in biology and chemistry. It regulates the movement of ions across cell membranes. This movement is influenced by two factors:
The electrical gradient: The electrical gradient across cell membranes refers to the difference in electric charge between the inside and outside of a cell.  This difference drives the movement of ions towards or away from the cells. For instance, if the inside of the cell is more negatively charged relative to...
2.3K
Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models00:57

Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models

80
Physiological pharmacokinetic models, often called flow-limited or perfusion models, typically assume a swift drug distribution between tissue and venous blood, creating a rapid drug equilibrium. This premise is based on the idea that drug diffusion is extremely fast, and the cell membrane presents no barrier to drug permeation. In this scenario, where no drug binding occurs, the drug concentration in the tissue equals that of the venous blood leaving the tissue. This greatly simplifies the...
80

You might also read

Related Articles

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

Sort by
Same author

Accurate mean-field equation for voter model dynamics on scale-free networks.

Physical review. E·2026
Same author

Cancer detection via one-shot learning: integrating gene expression and genomic mutation analysis.

BMC bioinformatics·2025
Same author

Investigating Endogenous Opioids Unravels the Mechanisms Behind Opioid-Induced Constipation, a Mathematical Modeling Approach.

International journal of molecular sciences·2025
Same author

Parameter Optimization for a Neurotransmission Recovery Model.

Bulletin of mathematical biology·2025
Same author

Independently engaging protein tethers of different length enhance synaptic vesicle trafficking to the plasma membrane.

The Journal of physiology·2025
Same author

Exploring transcription modalities from bimodal, single-cell RNA sequencing data.

NAR genomics and bioinformatics·2024

Related Experiment Video

Updated: Jul 5, 2025

Modeling Fast-scan Cyclic Voltammetry Data from Electrically Stimulated Dopamine Neurotransmission Data Using QNsim1.0
07:41

Modeling Fast-scan Cyclic Voltammetry Data from Electrically Stimulated Dopamine Neurotransmission Data Using QNsim1.0

Published on: June 5, 2017

9.9K

Partial mean-field model for neurotransmission dynamics.

Alberto Montefusco1, Luzie Helfmann1, Toluwani Okunola2

  • 1Mathematics of Complex Systems, Zuse-Institut Berlin, Takustraße 7, Berlin, 14195, Germany.

Mathematical Biosciences
|January 14, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces hybrid models combining particle-based and continuous methods for complex reaction networks. These hybrid models efficiently simulate systems with both high and low molecule counts, improving computational accuracy.

Keywords:
Hybrid modelingNeurotransmissionPartial differential equationStochastic processes

More Related Videos

3D Modeling of Dendritic Spines with Synaptic Plasticity
07:13

3D Modeling of Dendritic Spines with Synaptic Plasticity

Published on: May 18, 2020

6.9K
Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches
10:50

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Published on: June 21, 2022

1.8K

Related Experiment Videos

Last Updated: Jul 5, 2025

Modeling Fast-scan Cyclic Voltammetry Data from Electrically Stimulated Dopamine Neurotransmission Data Using QNsim1.0
07:41

Modeling Fast-scan Cyclic Voltammetry Data from Electrically Stimulated Dopamine Neurotransmission Data Using QNsim1.0

Published on: June 5, 2017

9.9K
3D Modeling of Dendritic Spines with Synaptic Plasticity
07:13

3D Modeling of Dendritic Spines with Synaptic Plasticity

Published on: May 18, 2020

6.9K
Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches
10:50

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Published on: June 21, 2022

1.8K

Area of Science:

  • Computational biology
  • Biophysics
  • Chemical kinetics

Background:

  • Particle-based models offer high accuracy for reaction networks but are computationally expensive.
  • Coarse-grained models reduce computational load but may lose microscopic detail.
  • Hybrid models are needed to balance accuracy and efficiency in complex biological systems.

Purpose of the Study:

  • To develop and validate a novel hybrid model for reaction-diffusion systems.
  • To integrate particle-based and continuous-resolution models.
  • To accurately simulate systems with varying molecular species counts.

Main Methods:

  • Development of a hybrid model combining particle-based and continuous (PDE) approaches.
  • Implementation of a particle-based model for ion and vesicle dynamics in neurotransmission.
  • Numerical experiments to compare hybrid model performance against full particle-based simulations.

Main Results:

  • The hybrid model successfully combines high-resolution particle tracking with macroscopic equation-based descriptions.
  • Accurate approximation of full particle-based model results was achieved in realistic scenarios.
  • Demonstrated efficiency gains for systems with large particle numbers.

Conclusions:

  • Hybrid models offer a computationally efficient and accurate approach for simulating complex reaction networks.
  • This method is particularly advantageous for biological systems with species exhibiting diverse abundance levels.
  • The developed hybrid model provides a powerful tool for studying processes like neurotransmission.