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 Videos

A basic biophysical model for bursting neurons

E Av-Ron1, H Parnas, L A Segel

  • 1Department of Applied Mathematics and Computer Science, Weizmann Institute of Science, Rehovot, Israel.

Biological Cybernetics
|January 1, 1993
PubMed
Summary
This summary is machine-generated.

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

A novel, extremely fast, feedback inhibition of glutamate release in the crayfish neuromuscular junction.

Neuroscience·2010
Same author

A theoretical experimental method to determine the locus of desensitization.

Bulletin of mathematical biology·2007
Same author

Theory of fast neurotransmitter release control based on voltage-dependent interaction between autoreceptors and proteins of the exocytotic machinery.

Bulletin of mathematical biology·2007
Same author

G-CSF control of neutrophils dynamics in the blood.

Bulletin of mathematical biology·2007
Same author

Role of NSF in neurotransmitter release: a peptide microinjection study at the crayfish neuromuscular junction.

Journal of neurophysiology·2006
Same author

Depolarization initiates phasic acetylcholine release by relief of a tonic block imposed by presynaptic M2 muscarinic receptors.

Journal of neurophysiology·2005
Same journal

Harmonic memory in phasor neural networks.

Biological cybernetics·2026
Same journal

Correction: Decreased spinal inhibition leads to undiversified locomotor patterns.

Biological cybernetics·2026
Same journal

Foundational issues of network models in biology.

Biological cybernetics·2026
Same journal

Dynamical mechanisms for coordinating long-term working memory based on the precision of spike-timing in cortical neurons.

Biological cybernetics·2026
Same journal

Distinct dopaminergic spike-timing-dependent plasticity rules are suited to different functional roles.

Biological cybernetics·2026
Same journal

Fluctuation-response relations for a two-stage population of spiking neurons stimulated by common noise.

Biological cybernetics·2026
See all related articles

This study introduces a biophysical cell model for bursting behavior, extending previous work on cell excitability. The model accurately describes various bursting patterns by adjusting key parameters like oscillation and quiescence durations.

Area of Science:

  • Computational neuroscience
  • Biophysics
  • Mathematical modeling

Background:

  • Neuronal excitability and oscillations are fundamental to brain function.
  • Previous models have described cell excitability and oscillations but not bursting.
  • Bursting is a complex firing pattern observed in various neuron types.

Purpose of the Study:

  • To present a basic biophysical cell model specifically designed to simulate bursting behavior.
  • To extend a previously established model for neuronal excitability and oscillations.
  • To demonstrate the model's ability to capture diverse bursting patterns.

Main Methods:

  • Development of a biophysical cell model incorporating key ion channel dynamics.
  • Systematic variation of a limited set of model parameters.

Related Experiment Videos

  • Analysis of model output to characterize burst cycle, oscillation duration, quiescence duration, and firing frequency.
  • Main Results:

    • The model successfully reproduces various patterns of neuronal bursting.
    • Parameter adjustments allow for precise control over burst cycle characteristics.
    • The model captures the interplay between oscillation and quiescence phases in bursting.

    Conclusions:

    • The developed biophysical model provides a valuable tool for studying neuronal bursting.
    • The model's flexibility allows for the investigation of different bursting mechanisms.
    • This work advances our understanding of the biophysical underpinnings of neuronal firing patterns.