Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Neural Circuits

Neural Circuits

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...

Electrical Synapses

Electrical Synapses

Electrical synapses found in all nervous systems play important and unique roles. In these synapses, the presynaptic and postsynaptic membranes are very close together (3.5 nm) and are actually physically connected by channel proteins forming gap junctions.
Gap junctions allow the current to pass directly from one cell to the next. In contrast, in the chemical synapse, the neurotransmitters carry the information through the synaptic cleft from one neuron to the next. They consist of two...

You might also read

Related Articles

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

Sort by

Same author

CDK9 degrader induces BRCAness and sensitizes castration-resistant prostate cancer to PARP inhibitor.

Theranostics·2026

Same author

AtHSPR Plays a Positive Role in Arabidopsis Resistance Against <i>Pseudomonas syringae</i> pv. <i>tomato</i> DC3000 by Interacting with TOP1.

Biomolecules·2026

Same author

Multiphysics Investigation on Thermal Characteristics of Internal Bio-Inspired V-Ribbed Cooling Channels for Outer Rotor PMSM.

Biomimetics (Basel, Switzerland)·2026

Same author

Precise Structure Regulation Induced Morphological Ordering Enables All-Polymer Solar Cells With 20.29% Efficiency and Extreme Mechanical Robustness.

Angewandte Chemie (International ed. in English)·2026

Same author

Without Paired Labeled Data: End-to-End Self-Supervised Learning for Drone-View Geo-Localization.

IEEE transactions on neural networks and learning systems·2026

Same author

Delta external fixation as a suitable option for definitive fixation of osteoporotic pilon fractures in biomechanics: a finite element analysis.

Frontiers in bioengineering and biotechnology·2026

Same journal

Exploiting audio-visual modalities in videos: Object detection via multi-stage bilateral coupling network.

Neural networks : the official journal of the International Neural Network Society·2026

Same journal

Reliability-aware modality completion with cross-modal distillation for federated learning with missing modalities.

Neural networks : the official journal of the International Neural Network Society·2026

Same journal

IGFD-Net: Illumination-guided frequency decoupling for polarization image fusion.

Neural networks : the official journal of the International Neural Network Society·2026

Same journal

Multiple-Strategies dung beetle optimizer and its applications in engineering optimization and bankruptcy prediction.

Neural networks : the official journal of the International Neural Network Society·2026

Same journal

Aggregating global-scale pixel-wise forgery cues within a graph.

Neural networks : the official journal of the International Neural Network Society·2026

Same journal

Finite-Time intermittent control for secure synchronization of Neutral-Type stochastic delayed neural networks under aperiodic DoS attacks.

Neural networks : the official journal of the International Neural Network Society·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Oct 1, 2025

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Published on: June 21, 2022

Modeling learnable electrical synapse for high precision spatio-temporal recognition.

Zhenzhi Wu¹, Zhihong Zhang², Huanhuan Gao²

¹Lynxi Technologies, Beijing 100097, China.

Neural Networks : the Official Journal of the International Neural Network Society

|March 6, 2022

Summary

This summary is machine-generated.

Introducing electrical synapses into artificial neural networks enhances performance on complex tasks. The novel ECLIF model improves accuracy in spatio-temporal processing, outperforming traditional Leaky Integrate and Fire networks.

Keywords:

Bio-plausible neuronal dynamics Electrical synapse/coupling Leaky-integrate-and-fire model Spatio-temporal information

More Related Videos

A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions

A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions

Published on: March 25, 2014

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

Published on: March 8, 2024

Related Experiment Videos

Last Updated: Oct 1, 2025

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Published on: June 21, 2022

A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions

A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions

Published on: March 25, 2014

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

Published on: March 8, 2024

Area of Science:

Computational Neuroscience
Artificial Intelligence
Spiking Neural Networks

Background:

Leaky Integrate and Fire (LIF) models are key for spatio-temporal tasks in artificial neural networks.
Current LIF networks primarily model chemical synapses, neglecting the role of electrical synapses.
Electrical synapses are crucial for neural coordination and action potential synchronization in biological systems.

Purpose of the Study:

To model electrical synapses within artificial Leaky Integrate and Fire neurons.
To introduce a refined neural model, ECLIF, incorporating electrical synapse dynamics.
To evaluate the impact of electrical synapses on the accuracy of deep neural networks for spatio-temporal tasks.

Main Methods:

Proposed the Extended Leaky Integrate and Fire (ECLIF) model, where membrane potentials propagate via convolution.
Developed deep networks utilizing the ECLIF model.
Trained the networks using the back-propagation-through-time algorithm.

Main Results:

The ECLIF model demonstrated significant accuracy improvements over traditional LIF networks.
High accuracy was achieved across five diverse datasets.
The inclusion of electrical synapses proved beneficial for spatio-temporal processing.

Conclusions:

Modeling electrical synapses is vital for enhancing artificial neural network performance on realistic spatio-temporal tasks.
The ECLIF model offers a promising approach for more biologically plausible and effective neural computation.
Electrical synapses play a critical role in achieving high accuracy in complex, time-dependent learning scenarios.