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Related Concept Videos

Neural Circuits01:25

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...
Propagation of Action Potentials01:23

Propagation of Action Potentials

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...

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Related Experiment Video

Updated: Jul 8, 2026

Viral Tracing of Genetically Defined Neural Circuitry
13:06

Viral Tracing of Genetically Defined Neural Circuitry

Published on: October 17, 2012

Sigma-delta cellular neural network for 2D modulation.

Hisashi Aomori1, Tsuyoshi Otake, Nobuaki Takahashi

  • 1Department of Electrical and Electronics Engineering, Sophia University, 7-1 Kioi-cho, Chiyoda-ku, Tokyo 102-8554, Japan. aomori@ieee.org

Neural Networks : the Official Journal of the International Neural Network Society
|January 25, 2008
PubMed
Summary

This study introduces a novel 2D sigma-delta modulation technique using discrete-time cellular neural networks (DT-CNNs). This spatial domain approach enables super-parallel processing for enhanced image reconstruction.

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Last Updated: Jul 8, 2026

Viral Tracing of Genetically Defined Neural Circuitry
13:06

Viral Tracing of Genetically Defined Neural Circuitry

Published on: October 17, 2012

Area of Science:

  • Electrical Engineering
  • Signal Processing
  • Computational Neuroscience

Background:

  • Sigma-delta modulation is prevalent for 1D analog-to-digital conversion.
  • Digital signal processing offers significant advantages for 2D signals in applications like image and medical imaging.
  • Existing sigma-delta modulation techniques are limited to one-dimensional signals.

Purpose of the Study:

  • To develop a true 2D sigma-delta modulation system.
  • To leverage spatial domain processing for 2D signals.
  • To utilize discrete-time cellular neural networks (DT-CNNs) for 2D sigma-delta modulation.

Main Methods:

  • Implementation of spatial domain sigma-delta modulation using DT-CNNs.
  • Utilizing A-template for digital-to-analog conversion (DAC) and C-template as an integrator.
  • Employing a nonlinear output function for bilevel output and CNN's spatial connectivity for parallel processing.

Main Results:

  • Demonstrated the feasibility of 2D sigma-delta modulation in the spatial domain.
  • The proposed architecture functions as a large-scale, super-parallel sigma-delta modulator.
  • Experimental results confirm excellent signal reconstruction performance.

Conclusions:

  • Cellular Neural Networks (CNNs) are highly capable of implementing sigma-delta modulators for 2D signals.
  • The proposed spatio-temporal dynamics achieve optimal signal reconstruction.
  • This approach offers a powerful new method for 2D signal processing.