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...

Design Example: Capacitance Multiplier Circuit

Design Example: Capacitance Multiplier Circuit

In integrated circuit technology, a capacitance multiplier is often utilized to produce a larger capacitance value when a small physical capacitance falls short. This is achieved by a circuit that multiplies capacitance values by a factor of up to 1000, such that a 10-pF capacitor can replicate the performance of a 100-nF capacitor.
The circuit illustrated in Figure 1 below incorporates two op-amps, with the first operating as a voltage follower and the second acting as an inverting amplifier.

You might also read

Related Articles

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

Sort by

Same author

Sleep microstructure correlates of the first-night effect: sleep spindles and slow-wave activity in healthy adults.

Sleep & breathing = Schlaf & Atmung·2026

Same author

Master stability functions for torus and stable equilibrium attractors.

Physical review. E·2026

Same author

Altered Erythrocyte Function via TLR9-ox-mtDNA Binding Links Mitochondrial Oxidative Damage to Systemic Inflammation in Multiple Sclerosis.

Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics·2026

Same author

Evolutionary history and genomic consequences of polyploidization in natural populations of <i>Orychophragmus taibaiensis</i>.

Horticulture research·2026

Same author

Reconfigurable Multiscroll Memristive Neural Network With Application to Telemedicine Privacy Protection.

IEEE transactions on cybernetics·2026

Same author

Neuronal TLR4 upregulation activates the cGAS-STING pathway to induce ferroptosis in EAE mice.

International immunopharmacology·2026

Same journal

Granular Ball-Based Noise-Resistant Fuzzy Multineighborhood Feature Selection via Label Enhancement and Feature Graph.

IEEE transactions on neural networks and learning systems·2026

Same journal

Fighting Evolving Spam With ARTMAP Models: A Noise-Resilient Online Detection Framework.

IEEE transactions on neural networks and learning systems·2026

Same journal

HyperSAT: Unsupervised Hypergraph Neural Networks for Weighted MaxSAT Problems.

IEEE transactions on neural networks and learning systems·2026

Same journal

Negation of Basic Belief Assignment in Multisource Information Fusion on Dempster-Shafer Theory With Applications in Pattern Classification.

IEEE transactions on neural networks and learning systems·2026

Same journal

Intervention Feasible Region and Driver Risk Capacity Aware Human-Machine Collaborative Safe Trajectory Planning.

IEEE transactions on neural networks and learning systems·2026

Same journal

A Unified Differential Denoising Learning Framework With a Pre-Trained Model and Fuzzy Graph Networks for Drug-Drug Interaction Prediction.

IEEE transactions on neural networks and learning systems·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Sep 18, 2025

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes

Published on: March 9, 2019

Generating Simple Cyclic Memristive Neural Network Circuit With Controllable Multiscroll Attractors and Multivariable

Qiang Lai, Yudi Xu, Luigi Fortuna

IEEE Transactions on Neural Networks and Learning Systems

|June 24, 2025

Summary

This summary is machine-generated.

This study introduces a novel memristive neural network circuit capable of generating complex multiscroll chaotic attractors. The design offers a simpler, more implementable alternative for neuromorphic computing applications.

More Related Videos

A Method for Growing Bio-memristors from Slime Mold

A Method for Growing Bio-memristors from Slime Mold

Published on: November 2, 2017

Using Neuron Spiking Activity to Trigger Closed-Loop Stimuli in Neurophysiological Experiments

Using Neuron Spiking Activity to Trigger Closed-Loop Stimuli in Neurophysiological Experiments

Published on: November 12, 2019

Related Experiment Videos

Last Updated: Sep 18, 2025

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes

Published on: March 9, 2019

A Method for Growing Bio-memristors from Slime Mold

A Method for Growing Bio-memristors from Slime Mold

Published on: November 2, 2017

Using Neuron Spiking Activity to Trigger Closed-Loop Stimuli in Neurophysiological Experiments

Using Neuron Spiking Activity to Trigger Closed-Loop Stimuli in Neurophysiological Experiments

Published on: November 12, 2019

Area of Science:

Neuroscience
Chaos Theory
Electronic Engineering

Background:

Memristors exhibit synaptic properties, making them suitable for neuromorphic circuits like neural networks.
Existing complex dynamic neural networks often suffer from high dimensionality and excessive connections, hindering practical implementation.

Purpose of the Study:

To design a simple cyclic memristive neural network (SCMNN) circuit capable of generating complex multiscroll chaotic attractors.
To overcome the implementation challenges of high-dimensional neural network circuits.

Main Methods:

Incorporating an arctangent function memristor into a simple cyclic neural network (SCNN).
Utilizing an external stimulus current to generate multiscroll attractors.
Activating switches in the memristor equivalent circuit to control the number of scrolls.

Main Results:

The designed SCMNN successfully generates multiscroll chaotic attractors.
The number of scrolls expands with activated switches and can be controlled via parameter variation.
The circuit demonstrates anti-interference capabilities and achieved multivariable amplitude control.
Experimental validation using a microcontroller and oscilloscope confirmed attractor generation.

Conclusions:

The proposed SCMNN circuit offers a viable and implementable approach for generating complex chaotic dynamics.
The circuit's ability to produce controllable multiscroll attractors holds potential for advanced neuromorphic applications.
NIST testing verified the circuit's application value in engineering.