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...

Parallel Processing

Parallel Processing

The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...

Propagation of Action Potentials

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...

You might also read

Related Articles

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

Sort by

Same author

Long-term outcome of persons with diabetic and non-diabetic neuro-osteoarthropathy after foot correction using external fixation.

Diabetic medicine : a journal of the British Diabetic Association·2020

Same author

Changes in incidence of severe hypoglycaemia in people with type 2 diabetes from 2006 to 2016: analysis based on health insurance data in Germany considering the anti-hyperglycaemic medication.

Diabetic medicine : a journal of the British Diabetic Association·2020

Same author

Diabetes-related distress is reduced in people with type 1, but not type 2 diabetes after participating in a diabetes treatment and teaching programme.

Diabetes & metabolism·2017

Same author

Increase in the incidence of severe hypoglycaemia in people with Type 2 diabetes in spite of new drugs: analysis based on health insurance data from Germany.

Diabetic medicine : a journal of the British Diabetic Association·2017

Same author

Diabetes-related burden and distress in people with diabetes mellitus at primary care level in Germany.

Acta diabetologica·2017

Same author

Successful endoscopic ultrasound-guided ethanol ablation of a symptomatic sporadic insulinoma in a patient with severe comorbidities not suitable for pancreatic surgery.

Diabetes & metabolism·2017

Same journal

Universal perceptron and DNA-like learning algorithm for binary neural networks: LSBF and PBF implementations.

IEEE transactions on neural networks·2013

Same journal

Guest editorial: special section on white box nonlinear prediction models.

IEEE transactions on neural networks·2011

Same journal

Data-based fault-tolerant control of high-speed trains with traction/braking notch nonlinearities and actuator failures.

IEEE transactions on neural networks·2011

Same journal

Guest editorial: special section on data-based control, modeling, and optimization.

IEEE transactions on neural networks·2011

Same journal

Neural network-based multiple robot simultaneous localization and mapping.

IEEE transactions on neural networks·2011

Same journal

Data-driven model-free adaptive control for a class of MIMO nonlinear discrete-time systems.

IEEE transactions on neural networks·2011

See all related articles

Search research articles

Related Experiment Video

Updated: Jul 7, 2026

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

Fast neural net simulation with a DSP processor array.

U A Muller¹, A Gunzinger, W Guggenbuhl

¹Electron. Lab., Swiss Federal Inst. of Technol., Zurich.

IEEE Transactions on Neural Networks

|January 1, 1995

Summary

This summary is machine-generated.

A new parallel computer, MUSIC, accelerates neural network simulations significantly. This powerful, energy-efficient system offers researchers unprecedented personal computing performance for complex AI tasks.

More Related Videos

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: Jul 7, 2026

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

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:

Computer Science
Artificial Intelligence
Parallel Computing

Background:

Traditional neural network simulations require substantial computational resources.
Existing parallel systems may not offer sufficient performance or accessibility for individual researchers.

Purpose of the Study:

To implement a high-speed neural network simulator on a novel parallel distributed-memory computer.
To evaluate the performance and efficiency of the MUSIC system for neural network applications.

Main Methods:

Development and implementation of a neural network simulator on the MUSIC (multiprocessor system with intelligent communication) parallel computer.
Utilizing a 60-processor system with 32-b floating-point precision for backpropagation algorithm execution.

Main Results:

Achieved 330 million connection updates per second (continuous weight update) and 1.4 Gflops sustained performance.
The system demonstrates a peak performance of 3.8 Gflops while consuming less than 800 W.
MUSIC fits into a 19-in rack, offering supercomputer-level speed as a personal desktop system.

Conclusions:

The MUSIC system provides researchers with previously unattainable personal computing performance for neural network simulations.
Its energy efficiency, compact size, and real-time interfaces make it suitable for both research and embedded applications.