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

Neural Circuits01:25

Neural Circuits

2.6K
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...
2.6K
Propagation of Action Potentials01:23

Propagation of Action Potentials

8.8K
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...
8.8K
The Role of Ion Channels in Neuronal Computation01:19

The Role of Ion Channels in Neuronal Computation

3.6K
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....
3.6K

You might also read

Related Articles

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

Sort by
Same author

Compact Second-Harmonic Generation in the C‑Exciton Band of 3R-MoS<sub>2</sub> for Integrated Quantum Photonics.

ACS photonics·2026
Same author

Novel Highly Efficient Buried Gratings for Selective Coupling of SPP Waves onto Single Interfaces.

Nanomaterials (Basel, Switzerland)·2024
Same author

Photorefraction Simulates Well the Plasticity of Neural Synaptic Connections.

Biomimetics (Basel, Switzerland)·2024
Same author

A Statistical Approach for <i>A-Posteriori</i> Deployment of Microclimate Sensors in Museums: A Case Study.

Sensors (Basel, Switzerland)·2022
Same author

Development of intellectual and scientific abilities through game-programming in Minecraft.

Education and information technologies·2022
Same author

Novel Model Based on Artificial Neural Networks to Predict Short-Term Temperature Evolution in Museum Environment.

Sensors (Basel, Switzerland)·2022

Related Experiment Video

Updated: Jan 13, 2026

Photodiode-Based Optical Imaging for Recording Network Dynamics with Single-Neuron Resolution in Non-Transgenic Invertebrates
10:18

Photodiode-Based Optical Imaging for Recording Network Dynamics with Single-Neuron Resolution in Non-Transgenic Invertebrates

Published on: July 9, 2020

3.3K

Learning Dynamics of Solitonic Optical Multichannel Neurons.

Alessandro Bile1, Arif Nabizada1, Abraham Murad Hamza1

  • 1Department of Fundamental and Applied Sciences for Engineering, Sapienza Università di Roma, 00161 Roma, Italy.

Biomimetics (Basel, Switzerland)
|October 28, 2025
PubMed
Summary

Researchers explored learning in optical neurons using spatial solitons. Single-node designs learn faster and more efficiently, while multi-node structures offer greater response diversity for photonic neuromorphic networks.

Keywords:
all-optical signal routingneuromorphic photonicsnonlinear waveguide circuitsphotonic neural networkssolitonic logic gatesspatial solitons

More Related Videos

Optical Recording of Suprathreshold Neural Activity with Single-cell and Single-spike Resolution
08:48

Optical Recording of Suprathreshold Neural Activity with Single-cell and Single-spike Resolution

Published on: September 5, 2012

12.3K
Silicon Nanowires and Optical Stimulation for Investigations of Intra- and Intercellular Electrical Coupling
08:58

Silicon Nanowires and Optical Stimulation for Investigations of Intra- and Intercellular Electrical Coupling

Published on: January 28, 2021

4.9K

Related Experiment Videos

Last Updated: Jan 13, 2026

Photodiode-Based Optical Imaging for Recording Network Dynamics with Single-Neuron Resolution in Non-Transgenic Invertebrates
10:18

Photodiode-Based Optical Imaging for Recording Network Dynamics with Single-Neuron Resolution in Non-Transgenic Invertebrates

Published on: July 9, 2020

3.3K
Optical Recording of Suprathreshold Neural Activity with Single-cell and Single-spike Resolution
08:48

Optical Recording of Suprathreshold Neural Activity with Single-cell and Single-spike Resolution

Published on: September 5, 2012

12.3K
Silicon Nanowires and Optical Stimulation for Investigations of Intra- and Intercellular Electrical Coupling
08:58

Silicon Nanowires and Optical Stimulation for Investigations of Intra- and Intercellular Electrical Coupling

Published on: January 28, 2021

4.9K

Area of Science:

  • Photonics and Optical Engineering
  • Computational Neuroscience
  • Materials Science

Background:

  • Optical neurons offer a pathway to co-localize memory and computation.
  • Spatial solitons in lithium niobate provide a robust platform for optical signal manipulation.
  • Understanding learning dynamics is crucial for developing advanced neuromorphic systems.

Purpose of the Study:

  • To analyze the learning dynamics of multichannel optical neurons.
  • To compare single-node and multi-node configurations for learning efficiency.
  • To investigate the impact of topological complexity and optical parameters on neuron performance.

Main Methods:

  • Simulations of optical neuron learning dynamics.
  • Utilizing spatial solitons in lithium niobate crystals.
  • Comparing configurations of varying topological complexity (3x3, 4x4, 5x5).

Main Results:

  • Single-node optical neurons demonstrated faster learning and lower energy consumption.
  • Multi-node configurations required higher intensities and longer timescales but produced more diverse responses.
  • Optical parameters were shown to effectively modulate device plasticity.

Conclusions:

  • Optical neuron design significantly influences learning speed and efficiency.
  • Multi-node structures can better mimic biological neural network functional diversity.
  • This research supports the development of all-optical photonic neuromorphic networks for on-chip learning and adaptive systems.