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

Long-term Potentiation01:25

Long-term Potentiation

2.7K
Long-term potentiation, or LTP, is one of the ways by which synaptic plasticity—changes in the strength of chemical synapses—can occur in the brain. LTP is the process of synaptic strengthening that occurs over time between pre and postsynaptic neuronal connections. The synaptic strengthening of LTP works in opposition to the synaptic weakening of long-term depression (LTD) and together are the main mechanisms that underlie learning and memory.
Hebbian LTP
LTP can occur when...
2.7K
Long-term Potentiation01:35

Long-term Potentiation

51.6K
Long-term potentiation, or LTP, is one of the ways by which synaptic plasticity—changes in the strength of chemical synapses—can occur in the brain. LTP is the process of synaptic strengthening that occurs over time between pre- and postsynaptic neuronal connections. The synaptic strengthening of LTP works in opposition to the synaptic weakening of long-term depression (LTD) and together are the main mechanisms that underlie learning and memory.
51.6K
Neuroplasticity01:01

Neuroplasticity

2.6K
Neuroplasticity reflects the brain's remarkable capacity to adapt and evolve, responding dynamically to learning, experiences, or injury by reorganizing its neural circuitry. This reorganization involves creating new neural connections and refining old ones through a series of biological processes that contribute to the brain's lifelong development and adaptability.
2.6K
Integration of Synaptic Events01:28

Integration of Synaptic Events

6.4K
Synaptic integration mainly includes the summation of graded potentials. Graded potentials, regardless of their type, cause subtle alterations in membrane voltage, resulting in either depolarization or hyperpolarization. These incremental changes, when combined or summed, can propel the neuron toward its threshold. Consider, for example, a membrane experiencing a +15 mV shift, causing it to depolarize from -70 mV to -55 mV. In this scenario, graded potentials govern the membrane's ability to...
6.4K
Long-term Depression01:05

Long-term Depression

27.3K
Long-term depression, or LTD, is one of the ways by which synaptic plasticity—changes in the strength of chemical synapses—can occur in the brain. LTD is the process of synaptic weakening that occurs over time between pre and postsynaptic neuronal connections. The synaptic weakening of LTD works in opposition to synaptic strengthening by long-term potentiation (LTP) and together are the main mechanisms that underlie learning and memory.
27.3K
Long-term Depression01:03

Long-term Depression

2.6K
Long-term depression, or LTD, is one of the ways by which synaptic plasticity—changes in the strength of chemical synapses—can occur in the brain. LTD is the process of synaptic weakening that occurs over time between pre and postsynaptic neuronal connections. The synaptic weakening of LTD works in opposition to synaptic strengthening by long-term potentiation (LTP) and together are the main mechanisms that underlie learning and memory.
Calcium Ion Concentration Mechanism
If over...
2.6K

You might also read

Related Articles

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

Sort by
Same author

Laplacian Dynamics and Kron Reduction in Species-Reaction Graphs of Chemical Reaction Networks.

Bulletin of mathematical biology·2026
Same author

Automated Hierarchical Block Decomposition of Biochemical Networks.

IEEE transactions on computational biology and bioinformatics·2025
Same author

Mathematical basis and toolchain for hierarchical optimization of biochemical networks.

PLoS computational biology·2024
Same author

A computational view of short-term plasticity and its implications for E-I balance.

Current opinion in neurobiology·2023
Same author

Using sensitivity analyses to understand bistable system behavior.

BMC bioinformatics·2023
Same author

Synthetic Data Resource and Benchmarks for Time Cell Analysis and Detection Algorithms.

eNeuro·2023
Same journal

Artificial intelligence-driven multi-omics analysis of gut-kidney axis in chronic kidney disease.

Progress in molecular biology and translational science·2026
Same journal

Artificial intelligence in multi-omics analysis of heart diseases.

Progress in molecular biology and translational science·2026
Same journal

AI in multi-omics analysis of type 2 diabetes.

Progress in molecular biology and translational science·2026
Same journal

AI in multi-omics analysis in AMR.

Progress in molecular biology and translational science·2026
Same journal

AI in multi-omics analysis of COVID-19 patient data.

Progress in molecular biology and translational science·2026
Same journal

AI in multi-omics analysis of liver diseases.

Progress in molecular biology and translational science·2026
See all related articles

Related Experiment Video

Updated: May 2, 2026

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

3D Modeling of Dendritic Spines with Synaptic Plasticity

Published on: May 18, 2020

6.7K

Multiscale modeling and synaptic plasticity.

Upinder S Bhalla1

  • 1National Centre for Biological Sciences, Bangalore, Karnataka, India.

Progress in Molecular Biology and Translational Science
|February 25, 2014
PubMed
Summary
This summary is machine-generated.

Multiscale modeling integrates multiple biological levels to understand synaptic plasticity, crucial for memory and neural recovery. This approach avoids oversimplification, offering new insights into complex neural processes.

Keywords:
BistabilityCompartmental modelHomeostasisPattern decodingReaction–diffusionSignaling networkStochastic

More Related Videos

Evaluation of Synaptic Multiplicity Using Whole-cell Patch-clamp Electrophysiology
10:52

Evaluation of Synaptic Multiplicity Using Whole-cell Patch-clamp Electrophysiology

Published on: April 23, 2019

12.8K
Implantation of a Cranial Window for Repeated In Vivo Imaging in Awake Mice
06:33

Implantation of a Cranial Window for Repeated In Vivo Imaging in Awake Mice

Published on: June 22, 2021

7.9K

Related Experiment Videos

Last Updated: May 2, 2026

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

3D Modeling of Dendritic Spines with Synaptic Plasticity

Published on: May 18, 2020

6.7K
Evaluation of Synaptic Multiplicity Using Whole-cell Patch-clamp Electrophysiology
10:52

Evaluation of Synaptic Multiplicity Using Whole-cell Patch-clamp Electrophysiology

Published on: April 23, 2019

12.8K
Implantation of a Cranial Window for Repeated In Vivo Imaging in Awake Mice
06:33

Implantation of a Cranial Window for Repeated In Vivo Imaging in Awake Mice

Published on: June 22, 2021

7.9K

Area of Science:

  • Neuroscience
  • Computational Biology
  • Systems Biology

Background:

  • Synaptic plasticity is central to memory, development, and neural recovery.
  • Previous models often oversimplify plasticity by focusing on single molecules or mechanisms.
  • Understanding plasticity requires integrating diverse biological scales.

Purpose of the Study:

  • To review multiscale modeling approaches in synaptic plasticity.
  • To discuss the technical landscape and implications of these models.
  • To highlight how multiscale modeling addresses the complexity of synaptic function.

Main Methods:

  • Review of existing literature on multiscale modeling of synaptic plasticity.
  • Analysis of diverse modeling strategies across different biological levels (molecular, cellular, systems).
  • Discussion of challenges in data integration and model specification.

Main Results:

  • Multiscale models acknowledge the interconnectedness of signaling pathways in synaptic plasticity.
  • These models provide deeper insights than single-level approaches.
  • Despite challenges, multiscale modeling has generated novel research questions.

Conclusions:

  • Multiscale modeling is essential for a comprehensive understanding of synaptic plasticity.
  • Integrating multiple biological scales is key to avoiding oversimplification in neuroscience.
  • Future research should focus on refining and applying multiscale models to complex neural phenomena.