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

Non-equilibrium in the Cell01:16

Non-equilibrium in the Cell

4.5K
An important concept in studying metabolism and energy is that of chemical equilibrium. Most chemical reactions are reversible. They can proceed in both directions, releasing energy into their environment in one direction, and absorbing it from the environment in the other direction. The same is true for the chemical reactions involved in cell metabolism, such as the breaking down and building up of proteins into and from individual amino acids, respectively. Reactants within a closed system...
4.5K
Neural Circuits01:25

Neural Circuits

1.3K
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...
1.3K
Neuronal Communication01:28

Neuronal Communication

1.0K
Neurons, the fundamental units of the brain and nervous system, communicate through complex electrochemical signals that underpin all cognitive and bodily functions. This communication is primarily facilitated by a process involving the generation and propagation of an action potential along the axon of the neuron. When the internal electrical charge of a neuron surpasses a certain threshold, an action potential is triggered. This rapid change in voltage travels swiftly along the axon to the...
1.0K
Introduction to Cognitive Psychology01:20

Introduction to Cognitive Psychology

525
Cognitive psychology is the field of psychology dedicated to examining how people think. It attempts to explain how and why we think the way we do by studying the interactions among human thinking, emotion, creativity, language, and problem-solving, as well as other cognitive processes. Cognitive psychology studies how information is processed and manipulated in remembering, thinking, and knowing.
This field emerged in the mid-20th century, following a period dominated by behaviorism, which...
525
Ampere-Maxwell's Law: Problem-Solving01:17

Ampere-Maxwell's Law: Problem-Solving

666
A parallel-plate capacitor with capacitance C, whose plates have area A and separation distance d, is connected to a resistor R and a battery of voltage V. The current starts to flow at t = 0. What is the displacement current between the capacitor plates at time t? From the properties of the capacitor, what is the corresponding real current?
To solve the problem, we can use the equations from the analysis of an RC circuit and Maxwell's version of Ampère's law.
For the first part of...
666

You might also read

Related Articles

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

Sort by
Same author

Motor cortex directly excites the substantia nigra pars reticulata, the basal ganglia output nucleus.

Nature communications·2026
Same author

A Neurocomputational Model of Observation-Based Decision Making with a Focus on Trust.

Brain sciences·2026
Same author

A highly energy-efficient multi-core neuromorphic architecture for training deep spiking neural networks.

Nature communications·2026
Same author

Multimodal learning with next-token prediction for large multimodal models.

Nature·2026
Same author

Synaptic integration and competition in the substantia nigra pars reticulata-An experimental and in silico analysis.

Proceedings of the National Academy of Sciences of the United States of America·2025
Same author

Neuromorphic computing paradigms enhance robustness through spiking neural networks.

Nature communications·2025
Same journal

Interplay between oxygen redox and interfacial stability of Li-rich positive electrodes in sulfide-based all-solid-state batteries.

Nature communications·2026
Same journal

Breaking dependence on melanisation imparts diversity to a dogmatic invasion strategy of phytopathogenic fungi.

Nature communications·2026
Same journal

Hydroxyl-rich nanocavities on perovskite enable nearly barrierless intramolecular hydrogen transfer for nitrate electroreduction to ammonia.

Nature communications·2026
Same journal

Household mobility responses to weather extremes in Kyrgyzstan.

Nature communications·2026
Same journal

Autonomous Motion Vision with Tri-bulk-heterojunctioned Organic Adaptation Transistor.

Nature communications·2026
Same journal

Tissue-adhesive hydrogel optical fiber for peripheral optogenetic neuromodulation.

Nature communications·2026
See all related articles

Related Experiment Video

Updated: Jul 16, 2025

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
11:18

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

Published on: March 2, 2015

10.3K

A GPU-based computational framework that bridges neuron simulation and artificial intelligence.

Yichen Zhang1, Gan He1, Lei Ma1,2

  • 1National Key Laboratory for Multimedia Information Processing, School of Computer Science, Peking University, Beijing, 100871, China.

Nature Communications
|September 18, 2023
PubMed
Summary
This summary is machine-generated.

A new Dendritic Hierarchical Scheduling (DHS) method significantly speeds up brain simulations. This GPU-accelerated approach enhances computational neuroscience and artificial intelligence model training.

More Related Videos

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches
10:50

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Published on: June 21, 2022

1.8K
Construction of an Improved Multi-Tetrode Hyperdrive for Large-Scale Neural Recording in Behaving Rats
10:04

Construction of an Improved Multi-Tetrode Hyperdrive for Large-Scale Neural Recording in Behaving Rats

Published on: May 9, 2018

11.4K

Related Experiment Videos

Last Updated: Jul 16, 2025

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
11:18

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

Published on: March 2, 2015

10.3K
Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches
10:50

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Published on: June 21, 2022

1.8K
Construction of an Improved Multi-Tetrode Hyperdrive for Large-Scale Neural Recording in Behaving Rats
10:04

Construction of an Improved Multi-Tetrode Hyperdrive for Large-Scale Neural Recording in Behaving Rats

Published on: May 9, 2018

11.4K

Area of Science:

  • Computational Neuroscience
  • Artificial Intelligence

Background:

  • Biophysically detailed multi-compartment models are crucial for understanding brain computation and developing AI algorithms.
  • High computational cost limits the application of these detailed models in neuroscience and AI.
  • Solving large systems of linear equations is a major simulation bottleneck.

Purpose of the Study:

  • To present a novel Dendritic Hierarchical Scheduling (DHS) method for accelerating simulations of detailed neural models.
  • To demonstrate the computational optimality and accuracy of the DHS method.
  • To introduce the DeepDendrite framework integrating DHS with the NEURON simulator for neuroscience applications.

Main Methods:

  • Developed and theoretically validated the Dendritic Hierarchical Scheduling (DHS) method.
  • Implemented DHS on a GPU-based platform, integrating it with the NEURON simulator to create the DeepDendrite framework.
  • Applied DeepDendrite to investigate spatial input patterns' effects on neuronal excitability in a detailed human pyramidal neuron model.

Main Results:

  • The DHS method achieves 2-3 orders of magnitude speedup compared to traditional CPU-based methods.
  • Theoretically proven computational optimality and accuracy of the DHS implementation.
  • Demonstrated successful application of DeepDendrite in neuroscience research and discussed its AI potential.

Conclusions:

  • The DHS method offers a significant acceleration for simulating complex neural models.
  • DeepDendrite provides an efficient framework for neuroscience research and AI development.
  • This approach enables efficient training of biophysically detailed models for tasks like image classification.