Jove
Visualize
Contact Us

Related Concept Videos

Integration of Synaptic Events01:28

Integration of Synaptic Events

1.7K
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...
1.7K
Neural Circuits01:25

Neural Circuits

1.4K
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...
1.4K
Sensory Perception: Organization of the Somatosensory System01:11

Sensory Perception: Organization of the Somatosensory System

3.2K
The somatosensory system is the central and peripheral nervous system component that senses and processes touch, pressure, pain, temperature, and body position or proprioception. The process of sensation takes place at three levels:
The receptor level:
The receptor level is the first stage of sensation. It involves the detection of a stimulus by specialized sensory receptors. The stimulus must arrive within the receptor's receptive field. Next, the receptor converts the energy of the...
3.2K
Frequency-dependent Selection01:21

Frequency-dependent Selection

22.1K
When the fitness of a trait is influenced by how common it is (i.e., its frequency) relative to different traits within a population, this is referred to as frequency-dependent selection. Frequency-dependent selection may occur between species or within a single species. This type of selection can either be positive—with more common phenotypes having higher fitness—or negative, with rarer phenotypes conferring increased fitness.
22.1K
Propagation of Action Potentials01:23

Propagation of Action Potentials

6.2K
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...
6.2K
Synaptic Signaling01:09

Synaptic Signaling

5.7K
Neurons communicate at synapses, or junctions, to excite or inhibit the activity of other neurons or target cells, such as muscles. Synapses may be chemical or electrical.
Most synapses are chemical, meaning an electrical impulse or action potential spurs the release of chemical messengers called neurotransmitters. The neuron sending the signal is called the presynaptic neuron, and the neuron receiving the signal is the postsynaptic neuron.
The presynaptic neuron fires an action potential that...
5.7K

You might also read

Related Articles

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

Sort by
Same author

Constrained inference in sparse coding reproduces contextual effects and predicts laminar neural dynamics.

PLoS computational biology·2019
Same journal

Detection, communication, and individual identification with deep audio embeddings: A case study with North Atlantic right whales.

PLoS computational biology·2026
Same journal

Exploring the structural lexicon of the Proteome via Metric Geometry.

PLoS computational biology·2026
Same journal

Linking retinal sampling in neural encoding models to temporal profiles of visual processing in humans.

PLoS computational biology·2026
Same journal

CAdir: Joint clustering of cells and genes for single-cell transcriptomics with visualization-driven cluster quality assessment.

PLoS computational biology·2026
Same journal

Systematic design of auxotrophic strains and media conditions to probe metabolic functions in E. coli.

PLoS computational biology·2026
Same journal

Neuronal excitability and parameter variability in the Hodgkin-Huxley model.

PLoS computational biology·2026
See all related articles
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: Aug 10, 2025

Multi-electrode Array Recordings of Neuronal Avalanches in Organotypic Cultures
16:01

Multi-electrode Array Recordings of Neuronal Avalanches in Organotypic Cultures

Published on: August 1, 2011

26.5K

Synaptic self-organization of spatio-temporal pattern selectivity.

Mohammad Dehghani-Habibabadi1, Klaus Pawelzik1

  • 1Institute for Theoretical Physics, University of Bremen, Bremen, Germany.

Plos Computational Biology
|February 13, 2023
PubMed
Summary
This summary is machine-generated.

Synaptic plasticity mechanisms enable spiking neurons to learn and recognize specific spatio-temporal patterns. This self-organizing sensitivity provides robust pattern detection and long-term memory storage in neural networks.

More Related Videos

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

3D Modeling of Dendritic Spines with Synaptic Plasticity

Published on: May 18, 2020

6.9K
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

1.1K

Related Experiment Videos

Last Updated: Aug 10, 2025

Multi-electrode Array Recordings of Neuronal Avalanches in Organotypic Cultures
16:01

Multi-electrode Array Recordings of Neuronal Avalanches in Organotypic Cultures

Published on: August 1, 2011

26.5K
3D Modeling of Dendritic Spines with Synaptic Plasticity
07:13

3D Modeling of Dendritic Spines with Synaptic Plasticity

Published on: May 18, 2020

6.9K
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

1.1K

Area of Science:

  • Computational Neuroscience
  • Neural Networks
  • Synaptic Plasticity

Background:

  • Spiking model neurons can be optimized for specific spatio-temporal spike pattern recognition.
  • The capability of biological synaptic plasticity mechanisms to achieve this temporal coding remains unclear.

Purpose of the Study:

  • To investigate if existing synaptic plasticity mechanisms can enable neurons to become sensitive to specific input spike patterns.
  • To explore the self-organization of temporal pattern detection and memory robustness in neural networks.

Main Methods:

  • Simulations of spiking model neurons incorporating Hebbian mechanisms, hetero-synaptic plasticity, and synaptic scaling.
  • Analysis of how these plasticity rules influence synaptic efficacies and neuronal responses to spatio-temporal input patterns.

Main Results:

  • A combination of Hebbian mechanisms, hetero-synaptic plasticity, and synaptic scaling is sufficient for self-organizing sensitivity to repeating spatio-temporal spike patterns.
  • Hetero-synaptic plasticity promotes specialization and faithful representation of pattern sequences in neuronal populations.
  • Pattern detection demonstrates robustness against noise and distortions, with memories protected from overwriting during periods of pattern absence.

Conclusions:

  • The proposed combination of plasticity mechanisms supports precise temporal coding and computation in spiking neural networks.
  • This provides a potential explanation for the long-term robustness of memory traces in the brain despite continuous synaptic plasticity.
  • The findings enhance the plausibility of temporal coding as a fundamental mechanism in neural computation.