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

The Synapse02:47

The Synapse

133.2K
Neurons communicate with one another by passing on their electrical signals to other neurons. A synapse is the location where two neurons meet to exchange signals. At the synapse, the neuron that sends the signal is called the presynaptic cell, while the neuron that receives the message is called the postsynaptic cell. Note that most neurons can be both presynaptic and postsynaptic, as they both transmit and receive information.
133.2K
The Role of Ion Channels in Neuronal Computation01:19

The Role of Ion Channels in Neuronal Computation

3.9K
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....
3.9K
Plasticity00:58

Plasticity

3.1K
Plasticity is the property where an object loses its elasticity and undergoes irreversible deformation, even after the deformation forces are eliminated. If a material deforms irreversibly without increasing stress or load, then this is called ideal plasticity. For example, when a force is applied to an aluminum rod, it changes its shape, but it does not return to its original shape once the force is removed. Plastic deformation or ductility is thus a permanent deformation or change in the...
3.1K
Plasticizers01:31

Plasticizers

368
Water-reducers, or plasticizers, are chemical admixtures used in concrete to improve strength and workability. These additives reduce the water-cement ratio without compromising workability, lower the cement content while maintaining the same workability, or increase workability to assist concrete placement in inaccessible areas.
Plasticizers function by using surface-active agents to create repulsive electrostatic forces between cement particles. This dispersion enhances the concrete's...
368
Plastic Behavior01:21

Plastic Behavior

579
A material's elastic behavior is characterized by the disappearance of stress once the load is removed, allowing the material to return to its original state. However, when stress surpasses the yield point, yielding commences, marking the onset of plastic deformation or permanent set. This change from elastic to plastic behavior is influenced by the peak stress value and the duration before the load is removed. An intriguing observation occurs when a specimen is loaded, unloaded, and...
579
Plastic Deformations01:14

Plastic Deformations

444
It is essential to understand how structural members behave under plastic deformation when the bending stress exceeds the material's yield strength. This state of deformation permanently alters the shape of the member, in contrast to the linear elastic behavior observed before yielding. The strain at any point in the member is expressed in terms of maximum strain. Notably, the neutral axis, which coincides with the centroid during elastic bending, shifts away from the centroid under plastic...
444

You might also read

Related Articles

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

Sort by
Same author

Learning shapes neural geometry in the primate prefrontal cortex.

Nature neuroscience·2026
Same author

Distinct roles of cortical layer 5 subtypes in associative learning.

Nature communications·2026
Same author

Granule cells reorient cortical manifolds to separate contexts but preserve their geometry.

bioRxiv : the preprint server for biology·2026
Same author

Developing Topics.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2025
Same author

Hippocampus supports multi-task reinforcement learning under partial observability.

Nature communications·2025
Same author

Author Correction: Self-supervised predictive learning accounts for cortical layer-specificity.

Nature communications·2025

Related Experiment Video

Updated: Feb 4, 2026

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

3D Modeling of Dendritic Spines with Synaptic Plasticity

Published on: May 18, 2020

7.4K

Computational roles of plastic probabilistic synapses.

Milton Llera-Montero1, João Sacramento2, Rui Ponte Costa3

  • 1Computational Neuroscience Unit, Department of Computer Science, School of Computer Science, Electrical and Electronic Engineering, and Engineering Mathematics, Faculty of Engineering, University of Bristol, United Kingdom; Bristol Neuroscience, University of Bristol, United Kingdom; School of Psychological Science, Faculty of Life Sciences, University of Bristol, United Kingdom.

Current Opinion in Neurobiology
|October 12, 2018
PubMed
Summary

The brain utilizes probabilistic synapses, which adjust their strength over time. Understanding these plastic, probabilistic synapses is crucial for advancing computational neuroscience and artificial intelligence.

More Related Videos

Quantifying Synapses: an Immunocytochemistry-based Assay to Quantify Synapse Number
18:11

Quantifying Synapses: an Immunocytochemistry-based Assay to Quantify Synapse Number

Published on: November 16, 2010

36.7K
Visualization of Thalamocortical Axon Branching and Synapse Formation in Organotypic Cocultures
06:16

Visualization of Thalamocortical Axon Branching and Synapse Formation in Organotypic Cocultures

Published on: March 28, 2018

6.9K

Related Experiment Videos

Last Updated: Feb 4, 2026

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

3D Modeling of Dendritic Spines with Synaptic Plasticity

Published on: May 18, 2020

7.4K
Quantifying Synapses: an Immunocytochemistry-based Assay to Quantify Synapse Number
18:11

Quantifying Synapses: an Immunocytochemistry-based Assay to Quantify Synapse Number

Published on: November 16, 2010

36.7K
Visualization of Thalamocortical Axon Branching and Synapse Formation in Organotypic Cocultures
06:16

Visualization of Thalamocortical Axon Branching and Synapse Formation in Organotypic Cocultures

Published on: March 28, 2018

6.9K

Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Artificial Intelligence

Background:

  • Synaptic transmission's probabilistic nature is not well understood.
  • Recent research suggests the brain uses probabilistic synapses for specific functions.
  • Synaptic response statistics show specificity and plasticity.

Purpose of the Study:

  • To review experimental evidence on synaptic response statistics.
  • To explore computational theories on the function of plastic probabilistic synapses.
  • To propose future research directions for understanding probabilistic synapses.

Main Methods:

  • Review of experimental data on synaptic specificity and plasticity.
  • Overview of computational models for probabilistic synapse function.
  • Analysis of theoretical frameworks for synaptic plasticity optimization.

Main Results:

  • Probabilistic synapses exhibit specific and plastic response statistics.
  • Computational models link plastic probabilistic synapses to learning paradigms.
  • Optimization of probabilistic synapses is supported by plasticity experiments.

Conclusions:

  • Probabilistic synapses play a key role in brain computation.
  • Understanding these synapses is vital for advancing AI and neuroscience.
  • Further research is needed to fully elucidate their computational functions.