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

Propagation of Action Potentials01:23

Propagation of Action Potentials

15.7K
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...
15.7K
Neural Circuits01:25

Neural Circuits

3.3K
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...
3.3K
Postsynaptic Potential (PSP)01:32

Postsynaptic Potential (PSP)

11.5K
Postsynaptic potential (PSP) refers to a change in the electrical potential of a neuron when neurotransmitters released by presynaptic neurons bind to postsynaptic receptors. This potential can either be excitatory, leading to depolarization and ultimately action potential generation, or inhibitory, leading to hyperpolarization and suppression of the postsynaptic neuron.
There are two types of receptors: ionotropic and metabotropic.
The ionotropic receptor is the membrane protein that has an...
11.5K
Long-term Potentiation01:25

Long-term Potentiation

3.9K
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...
3.9K
Long-term Potentiation01:35

Long-term Potentiation

59.7K
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.
59.7K
Graded Potential01:19

Graded Potential

12.4K
Graded potentials are localized fluctuations in the cell membrane's electrical charge, commonly found in the dendrites of neurons. The magnitude of these potential changes depends on the strength of the initiating stimulus. In a membrane at its resting potential, a graded potential signifies a voltage shift either above -70 mV or below -70 mV.
Graded potentials fall into two categories: depolarizing and hyperpolarizing. Depolarizing graded potentials typically occur when sodium (Na+) or...
12.4K

You might also read

Related Articles

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

Sort by
Same author

Coherent Excitation of Exciton-Polariton Bound State in the Continuum via Optical Parametric Oscillation.

Nano letters·2025
Same author

Nonreciprocal Transport of Exciton Polaritons in a Non-Hermitian Chain.

Physical review letters·2020
Same author

Coupling between Exciton-Polariton Corner Modes through Edge States.

Physical review letters·2020
Same author

On the possibility of a terahertz light emitting diode based on a dressed quantum well.

Scientific reports·2019
Same author

Exciton-polariton topological insulator.

Nature·2018
Same author

Publisher Correction: Single-shot condensation of exciton polaritons and the hole burning effect.

Nature communications·2018

Related Experiment Video

Updated: Apr 15, 2026

Combined Shuttle-Box Training with Electrophysiological Cortex Recording and Stimulation as a Tool to Study Perception and Learning
08:43

Combined Shuttle-Box Training with Electrophysiological Cortex Recording and Stimulation as a Tool to Study Perception and Learning

Published on: October 22, 2015

10.9K

Perceptrons with Hebbian learning based on wave ensembles in spatially patterned potentials.

T Espinosa-Ortega1, T C H Liew1

  • 1Division of Physics and Applied Physics, Nanyang Technological University, Singapore 637371, Singapore.

Physical Review Letters
|April 4, 2015
PubMed
Summary

This study presents a novel perceptron design for hardware neural networks using Schrödinger wave superposition for interconnections. This approach enables compact optical system implementation for advanced computing applications.

More Related Videos

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology
09:44

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

Published on: March 8, 2024

6.2K
Neural Activity Propagation in an Unfolded Hippocampal Preparation with a Penetrating Micro-electrode Array
09:48

Neural Activity Propagation in an Unfolded Hippocampal Preparation with a Penetrating Micro-electrode Array

Published on: March 27, 2015

8.9K

Related Experiment Videos

Last Updated: Apr 15, 2026

Combined Shuttle-Box Training with Electrophysiological Cortex Recording and Stimulation as a Tool to Study Perception and Learning
08:43

Combined Shuttle-Box Training with Electrophysiological Cortex Recording and Stimulation as a Tool to Study Perception and Learning

Published on: October 22, 2015

10.9K
Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology
09:44

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

Published on: March 8, 2024

6.2K
Neural Activity Propagation in an Unfolded Hippocampal Preparation with a Penetrating Micro-electrode Array
09:48

Neural Activity Propagation in an Unfolded Hippocampal Preparation with a Penetrating Micro-electrode Array

Published on: March 27, 2015

8.9K

Area of Science:

  • Quantum Computing
  • Optical Physics
  • Artificial Intelligence Hardware

Background:

  • Current hardware neural networks face limitations in interconnection density and efficiency.
  • Developing compact and efficient hardware for artificial intelligence is crucial for advancing computing capabilities.

Purpose of the Study:

  • To propose a general scheme for realizing a perceptron suitable for hardware neural networks.
  • To leverage quantum phenomena for efficient information processing in artificial intelligence hardware.

Main Methods:

  • Utilizing the superposition of Schrödinger waves to achieve multiple interconnections.
  • Employing spatially patterned potentials to couple different points in reciprocal space for information processing.
  • Deriving the required potential shape from the Hebbian learning rule, either through exact calculation or by constructing it from known optical inputs.

Main Results:

  • Demonstrated a method for creating a perceptron using optical principles.
  • The proposed scheme allows for the implementation of interconnections through wave superposition.
  • Potential shapes are derived from established learning rules, facilitating practical application.

Conclusions:

  • The presented scheme offers a viable pathway for building compact optical perceptrons for hardware neural networks.
  • This approach is adaptable to various compact optical systems, including nonlinear optics, lithographically patterned systems, and exciton-polariton systems.
  • The findings pave the way for novel hardware implementations of artificial intelligence.