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 Role of Ion Channels in Neuronal Computation01:19

The Role of Ion Channels in Neuronal Computation

4.2K
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....
4.2K
Neuroplasticity01:01

Neuroplasticity

2.4K
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.
2.4K
Integration of Synaptic Events01:28

Integration of Synaptic Events

5.7K
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...
5.7K
Long-term Potentiation01:25

Long-term Potentiation

3.8K
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...
3.8K
Long-term Potentiation01:35

Long-term Potentiation

59.3K
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.
59.3K
Excitatory and Inhibitory Effects of Neurotransmitters01:29

Excitatory and Inhibitory Effects of Neurotransmitters

14.5K
When an action potential reaches the presynaptic axon terminal, it releases neurotransmitters from the neuron into the synaptic cleft at a chemical synapse. The released neurotransmitter can be excitatory or inhibitory. The critical criteria commonly used to determine whether a molecule is a neurotransmitter at a chemical synapse are the molecule's presence in the presynaptic neuron. Second, its release is in response to strong presynaptic depolarization. And lastly, the presence of...
14.5K

You might also read

Related Articles

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

Sort by
Same author

Virtual brain and electroencephalography explain the variance of memory alterations in mild cognitive impairment.

Alzheimer's research & therapy·2026
Same author

Measuring Electrophysiological Activity in Acute Brain Slices, Spheroids, and Organoids Using 3D High-Density Multielectrode Arrays.

Bio-protocol·2026
Same author

Alterations in topological and dynamical parameters correlate with disease biomarkers and neuropsychological scores in prodromic stages of dementia.

Scientific reports·2026
Same author

Toward future diagnostics of Parkinson's disease: a perspective on multimodal motor assessment and personalized digital twins.

Frontiers in aging neuroscience·2026
Same author

Data-driven mouse motor thalamus model reveals topography and spatial weight scaling govern spindle dynamics.

Communications biology·2026
Same author

Infants' spontaneous movements explore arm dynamics.

Communications biology·2026
Same journal

Latent Space Projections and Atlases, a Cautionary Tale in Deep Neuroimaging using Autoencoders.

International journal of neural systems·2026
Same journal

Transformer-Based Anomaly Detection for Neurodegenerative Screening in MRI Images.

International journal of neural systems·2026
Same journal

Discrete Wavelet Convolution for Learnable Time-Frequency Representation with Application to Seizure Prediction.

International journal of neural systems·2026
Same journal

Automatic Seizure Detection using Hierarchical Spectral-Temporal Feature Learning with an Imbalance-Aware Transformer.

International journal of neural systems·2026
Same journal

Pyramid Vision Transformer-Enhanced Conformer Network for Epileptic Seizure Recognition Using MultiChannel EEG Signals.

International journal of neural systems·2026
Same journal

A Time-Frequency Decoupled Contrastive Learning Framework for Electroencephalography-Based Parkinson's Disease Diagnosis.

International journal of neural systems·2026
See all related articles

Related Experiment Video

Updated: Mar 22, 2026

Inducing Long-Term Plasticity of Intrinsic Neuronal Excitability in Neurons of the Dorsal Lateral Geniculate Nucleus
05:01

Inducing Long-Term Plasticity of Intrinsic Neuronal Excitability in Neurons of the Dorsal Lateral Geniculate Nucleus

Published on: September 20, 2024

853

Oscillation-Driven Spike-Timing Dependent Plasticity Allows Multiple Overlapping Pattern Recognition in Inhibitory

Jesús A Garrido1, Niceto R Luque2,3, Silvia Tolu4

  • 11 Department of Computer Architecture and Technology, University of Granada, Periodista Daniel Saucedo Aranda s/n, Granada, 18071, Spain.

International Journal of Neural Systems
|April 16, 2016
PubMed
Summary
This summary is machine-generated.

Brain networks learn complex patterns using synaptic plasticity in interneurons, optimized by theta oscillations and homeostatic mechanisms for robust information processing and sparse representations.

Keywords:
Spiking neural networkintrinsic plasticitylateral inhibitionoscillationspattern recognitionspike-timing dependent plasticity

More Related Videos

Ex Vivo Optogenetic Interrogation of Long-Range Synaptic Transmission and Plasticity from Medial Prefrontal Cortex to Lateral Entorhinal Cortex
11:31

Ex Vivo Optogenetic Interrogation of Long-Range Synaptic Transmission and Plasticity from Medial Prefrontal Cortex to Lateral Entorhinal Cortex

Published on: February 25, 2022

3.0K
Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond
08:08

Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond

Published on: June 24, 2015

12.1K

Related Experiment Videos

Last Updated: Mar 22, 2026

Inducing Long-Term Plasticity of Intrinsic Neuronal Excitability in Neurons of the Dorsal Lateral Geniculate Nucleus
05:01

Inducing Long-Term Plasticity of Intrinsic Neuronal Excitability in Neurons of the Dorsal Lateral Geniculate Nucleus

Published on: September 20, 2024

853
Ex Vivo Optogenetic Interrogation of Long-Range Synaptic Transmission and Plasticity from Medial Prefrontal Cortex to Lateral Entorhinal Cortex
11:31

Ex Vivo Optogenetic Interrogation of Long-Range Synaptic Transmission and Plasticity from Medial Prefrontal Cortex to Lateral Entorhinal Cortex

Published on: February 25, 2022

3.0K
Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond
08:08

Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond

Published on: June 24, 2015

12.1K

Area of Science:

  • Computational neuroscience
  • Neural network modeling
  • Synaptic plasticity

Background:

  • Brain function relies on learning complex signal patterns for recognition and retrieval.
  • Long-term synaptic plasticity is crucial for learning, but its role in pattern recognition is unclear.

Purpose of the Study:

  • To investigate how synaptic plasticity in a simplified neural network model contributes to complex pattern recognition.
  • To explore the role of inhibitory interneurons and network oscillations in pattern storage and retrieval.

Main Methods:

  • Modeled a network of excitatory neurons and inhibitory interneurons with lateral inhibition.
  • Incorporated spike-timing dependent plasticity (STDP) at excitatory and inhibitory synapses.
  • Investigated the effect of theta-frequency oscillations and homeostatic plasticity on network function.

Main Results:

  • Interneurons rapidly learned complex input patterns when STDP was induced during theta oscillations.
  • Inhibitory plasticity enabled the distribution and simultaneous detection of multiple overlapping patterns.
  • Plasticity in intrinsic excitability enhanced robustness to varied input patterns.
  • Combined plasticity mechanisms optimized mutual information transfer and promoted sparse representations.

Conclusions:

  • Plasticity in inhibitory interneuron networks is critical for storing multiple complex patterns.
  • Theta-frequency oscillations provide a necessary phase reference for STDP-driven learning.
  • Network robustness and efficient information processing are achieved through combined plasticity and homeostatic mechanisms.