Jove
Visualize
Contact Us

Related Concept Videos

Propagation of Action Potentials01:23

Propagation of Action Potentials

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...
The Role of Ion Channels in Neuronal Computation01:19

The Role of Ion Channels in Neuronal Computation

A postsynaptic neuron usually receives numerous impulses from several other presynaptic neurons. The axon hillock of the postsynaptic neuron integrates all these signals and determines the likelihood of firing an action potential.
Sometimes a single EPSP is strong enough to induce an action potential in the postsynaptic neuron. However, multiple presynaptic inputs must often create EPSPs around the same time for the postsynaptic neuron to be sufficiently depolarized to fire an action potential.
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

New insights into chaos in Rulkov map.

Chaos (Woodbury, N.Y.)·2026
Same author

Olympiad-level formal mathematical reasoning with reinforcement learning.

Nature·2025
Same author

Two-player Yorke's game of survival in chaotic transients.

Physical review. E·2025
Same author

Noise-induced bursting near a crisis bifurcation in a map-based neuron model.

Physical review. E·2025
Same author

Fast and slow escapes in forced chaotic scattering: The Newtonian and the relativistic regimes.

Physical review. E·2025
Same author

Nuclear factor erythroid 2-related factor improves depression and cognitive dysfunction in rats with ischemic stroke by mediating wolfram syndrome 1.

Brain research·2025
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: Jul 3, 2026

Automated Multimodal Stimulation and Simultaneous Neuronal Recording from Multiple Small Organisms
08:28

Automated Multimodal Stimulation and Simultaneous Neuronal Recording from Multiple Small Organisms

Published on: March 3, 2023

Bursting regimes in map-based neuron models coupled through fast threshold modulation.

Borja Ibarz1, Hongjun Cao, Miguel A F Sanjuán

  • 1Nonlinear Dynamics and Chaos Group, Departamento de Física, Universidad Rey Juan Carlos, Tulipán s/n, 28933 Móstoles, Madrid, Spain. borja.ibarz@urjc.es

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|July 23, 2008
PubMed
Summary

This study explores how two coupled neurons synchronize their bursts. It reveals that synaptic properties like conductance and threshold significantly impact synchronization, with effects extending to larger neural networks.

More Related Videos

Contribution of the Na+/K+ Pump to Rhythmic Bursting, Explored with Modeling and Dynamic Clamp Analyses
08:34

Contribution of the Na+/K+ Pump to Rhythmic Bursting, Explored with Modeling and Dynamic Clamp Analyses

Published on: May 9, 2021

A Method for High Fidelity Optogenetic Control of Individual Pyramidal Neurons In vivo
13:44

A Method for High Fidelity Optogenetic Control of Individual Pyramidal Neurons In vivo

Published on: September 2, 2013

Related Experiment Videos

Last Updated: Jul 3, 2026

Automated Multimodal Stimulation and Simultaneous Neuronal Recording from Multiple Small Organisms
08:28

Automated Multimodal Stimulation and Simultaneous Neuronal Recording from Multiple Small Organisms

Published on: March 3, 2023

Contribution of the Na+/K+ Pump to Rhythmic Bursting, Explored with Modeling and Dynamic Clamp Analyses
08:34

Contribution of the Na+/K+ Pump to Rhythmic Bursting, Explored with Modeling and Dynamic Clamp Analyses

Published on: May 9, 2021

A Method for High Fidelity Optogenetic Control of Individual Pyramidal Neurons In vivo
13:44

A Method for High Fidelity Optogenetic Control of Individual Pyramidal Neurons In vivo

Published on: September 2, 2013

Area of Science:

  • Computational Neuroscience
  • Systems Neuroscience

Background:

  • Neural systems exhibit complex synchronized firing patterns crucial for information processing.
  • Understanding the mechanisms of neuronal synchronization is fundamental to neuroscience.

Purpose of the Study:

  • To investigate synchronization dynamics in a two-map-based neuron system with chemical synapses.
  • To identify biologically relevant regimes and effects of synaptic coupling.

Main Methods:

  • Simulated a two-neuron system with reciprocal excitatory or inhibitory chemical synapses.
  • Explored parameter space to analyze burst generation and synchronization.
  • Investigated the impact of synaptic conductance and threshold variations.

Main Results:

  • Excitatory synapses without delays can induce antiphase synchronization.
  • Synaptic character (excitatory/inhibitory) can be modulated by conductance.
  • Small changes in synaptic threshold cause significant alterations in spike synchronization within bursts.
  • Synchronization phenomena observed in the two-neuron system are scalable to larger networks.

Conclusions:

  • Synaptic properties play a critical role in determining neuronal synchronization patterns.
  • The explored two-neuron model provides insights into network-level synchronization dynamics.
  • Findings highlight the sensitivity of neural synchronization to synaptic parameters.