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

Presynaptic frequency- and pattern-dependent filtering.

Alex M Thomson1

  • 1Department of Pharmacology, The School of Pharmacy, London University, 29-39 Brunswick Square, London WC1N 1AX, UK. alex.thomson@ams1.ulsop.ac.uk

Journal of Computational Neuroscience
|September 27, 2003
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

Community-based reconstruction and simulation of a full-scale model of the rat hippocampus CA1 region.

PLoS biology·2024
Same author

Circuits and Synapses: Hypothesis, Observation, Controversy and Serendipity - An Opinion Piece.

Frontiers in neural circuits·2021
Same author

Data-driven integration of hippocampal CA1 synaptic physiology in silico.

Hippocampus·2020
Same author

The physiological variability of channel density in hippocampal CA1 pyramidal cells and interneurons explored using a unified data-driven modeling workflow.

PLoS computational biology·2018
Same author

Cornu Ammonis Regions-Antecedents of Cortical Layers?

Frontiers in neuroanatomy·2017
Same author

γ-Aminobutyric Acid Type A (GABAA) Receptor Subunits Play a Direct Structural Role in Synaptic Contact Formation via Their N-terminal Extracellular Domains.

The Journal of biological chemistry·2016
Same journal

Hierarchical learning creates invariant schema within plastic neural networks.

Journal of computational neuroscience·2026
Same journal

Intrinsic chaos control in cortical circuits: A minimal E-I-M rate model for primary visual cortex.

Journal of computational neuroscience·2026
Same journal

Modeling developmental spiking behavior driven by ionic current dynamics of mouse and human inner hair cells using a calcium-enhanced Izhikevich framework.

Journal of computational neuroscience·2026
Same journal

A biophysically grounded model of glutamatergic synaptic transmission integrating glutamate transport, receptor kinetics, and electrotonic effects.

Journal of computational neuroscience·2026
Same journal

When can neuronal activity-dependent homeostatic plasticity maintain circuit-level properties?

Journal of computational neuroscience·2026
Same journal

A charge conservative finite volume discretization of the Hodgkin-Huxley model.

Journal of computational neuroscience·2026
See all related articles

Synaptic transmission patterns depend on both pre- and postsynaptic neurons. Specific presynaptic mechanisms fine-tune how synapses respond to varying neural activity frequencies.

Area of Science:

  • Neuroscience
  • Synaptic Plasticity
  • Cellular Electrophysiology

Background:

  • Neuronal communication relies on synaptic transmission.
  • Synaptic connections exhibit diverse properties in transmitter release patterns.

Purpose of the Study:

  • Investigate the factors influencing frequency-dependent transmitter release.
  • Determine the roles of presynaptic and postsynaptic neurons in shaping synaptic properties.

Main Methods:

  • Dual intracellular recordings from synaptically connected neuron pairs.
  • Analysis of frequency-dependent transmitter release patterns.

Main Results:

  • Transmitter release patterns vary significantly across different synaptic connection types.

Related Experiment Videos

  • Postsynaptic neuronal class strongly influences, not just the presynaptic, frequency-dependent release patterns.
  • Identified diverse presynaptic mechanisms that either depress or enhance transmitter release.

    • Conclusions:

    • Synaptic connection properties are determined by the selective expression of various presynaptic release mechanisms.
    • Molecular interactions, including protein-protein and protein-lipid interactions, are crucial for tuning synaptic responses to specific neural activity patterns.