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

Neural Circuits01:25

Neural Circuits

2.2K
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...
2.2K
Neurons as Communicators of the Brain01:22

Neurons as Communicators of the Brain

2.4K
Neurons, the fundamental units of the brain and nervous system, function as the primary transmitters of information throughout the body. Their ability to communicate through electrical and chemical signals is vital for every bodily function, from regulating the heartbeat to processing complex thoughts. Each neuron has three main components: the cell body (soma), dendrites, and an axon, each specialized to facilitate swift and efficient neural communication.
Cell Body
The cell body, also known...
2.4K
Neuronal Communication01:28

Neuronal Communication

2.4K
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...
2.4K
Neurons: The Axon01:21

Neurons: The Axon

6.2K
Axons are long, cytoplasmic processes of nerve cells capable of propagating electrical impulses known as action potentials. The cytoplasm or axoplasm of an axon contains neurofibrils, neurotubules, small vesicles, lysosomes, mitochondria, and various enzymes, all encased within the axolemma, the plasma membrane of the axon.
The axon attaches to the cell body at a cone-shaped elevation called the axon hillock. The initial part of the axon, closest to the hillock, is known as the initial segment....
6.2K
Neural Regulation01:37

Neural Regulation

42.2K
Digestion begins with a cephalic phase that prepares the digestive system to receive food. When our brain processes visual or olfactory information about food, it triggers impulses in the cranial nerves innervating the salivary glands and stomach to prepare for food.
42.2K
Neuron Structure01:30

Neuron Structure

16.6K
Neurons are the main type of cell in the nervous system that generate and transmit electrochemical signals. They primarily communicate with each other using neurotransmitters at specific junctions called synapses. Neurons come in many shapes that often relate to their function, but most share three main structures: an axon and dendrites that extend out from a cell body.
Structure and Function of Neurons
The neuronal cell body—the soma— houses the nucleus and organelles vital to...
16.6K

You might also read

Related Articles

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

Sort by
Same author

Dataset-Learning Duality and Emergent Criticality.

Entropy (Basel, Switzerland)·2025
Same journal

Research on a Regional Availability Evaluation Model for Road-Area High-Entropy Energy Based on Synergy Factors.

Entropy (Basel, Switzerland)·2026
Same journal

Atmospheric Turbulence Channel Modeling and Performance Analysis of a CO-ZP-OFDM Coherent Optical Communication System for UAV Air-to-Ground Scenarios.

Entropy (Basel, Switzerland)·2026
Same journal

Information Geometry and Asymptotic Theory for SMML Estimators.

Entropy (Basel, Switzerland)·2026
Same journal

Correlation Entropy and Power-Law Kinetics.

Entropy (Basel, Switzerland)·2026
Same journal

Research on the Contagion of Systemic Financial Risk Under the Impact of Climate Risks-From the Perspective of Complex Networks and Machine Learning.

Entropy (Basel, Switzerland)·2026
Same journal

The Statistical-Mechanical Meaning of the Wave Function of Quantum Mechanics.

Entropy (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: Nov 27, 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

10.6K

The World as a Neural Network.

Vitaly Vanchurin1

  • 1Department of Physics, University of Minnesota, Duluth, Minnesota, MN 55812, USA.

Entropy (Basel, Switzerland)
|December 8, 2020
PubMed
Summary
This summary is machine-generated.

The universe may fundamentally be a neural network, with trainable and hidden variables exhibiting quantum and classical behaviors. This framework reveals emergent relativistic and curved spacetime dynamics, potentially linking quantum mechanics and general relativity.

Keywords:
general relativitymachine learningquantum mechanicsthermodynamics of learning

More Related Videos

Author Spotlight: Modular Neuronal Networks for Analyzing Brain Functions
07:38

Author Spotlight: Modular Neuronal Networks for Analyzing Brain Functions

Published on: June 7, 2024

2.0K
3D Scanning Technology Bridging Microcircuits and Macroscale Brain Images in 3D Novel Embedding Overlapping Protocol
10:14

3D Scanning Technology Bridging Microcircuits and Macroscale Brain Images in 3D Novel Embedding Overlapping Protocol

Published on: May 12, 2019

7.5K

Related Experiment Videos

Last Updated: Nov 27, 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

10.6K
Author Spotlight: Modular Neuronal Networks for Analyzing Brain Functions
07:38

Author Spotlight: Modular Neuronal Networks for Analyzing Brain Functions

Published on: June 7, 2024

2.0K
3D Scanning Technology Bridging Microcircuits and Macroscale Brain Images in 3D Novel Embedding Overlapping Protocol
10:14

3D Scanning Technology Bridging Microcircuits and Macroscale Brain Images in 3D Novel Embedding Overlapping Protocol

Published on: May 12, 2019

7.5K

Area of Science:

  • Theoretical Physics
  • Cosmology
  • Machine Learning

Background:

  • The fundamental nature of the universe remains a key question in physics.
  • Neural networks offer a novel framework for exploring complex systems.
  • Bridging quantum mechanics and general relativity is a major challenge.

Purpose of the Study:

  • To investigate the hypothesis that the universe is a neural network.
  • To explore the emergent properties of such a system.
  • To connect neural network dynamics with fundamental physics theories.

Main Methods:

  • Analyzing stochastic evolution of trainable and hidden variables in a neural network model.
  • Applying Madelung and Hamilton-Jacobi equations to describe variable dynamics.
  • Investigating emergent spacetime from subsystem interactions and Onsager tensor symmetries.

Main Results:

  • Trainable variables exhibit classical and quantum dynamics.
  • Hidden variables lead to emergent relativistic strings in Minkowski spacetime.
  • Interacting subsystems generate curved spacetime, with entropy production linked to the Einstein-Hilbert term.
  • Holographic duality between quantum and general relativity descriptions is proposed.

Conclusions:

  • A neural network model can reproduce key aspects of quantum mechanics and general relativity.
  • The learning dynamics of neural networks may offer insights into fundamental physics.
  • This framework suggests a potential unification of seemingly disparate physical theories.