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

Laminar and Turbulent Flow01:07

Laminar and Turbulent Flow

11.9K
Fluid dynamics is the study of fluids in motion. Velocity vectors are often used to illustrate fluid motion in applications like meteorology. For example, wind—the fluid motion of air in the atmosphere—can be represented by vectors indicating the speed and direction of the wind at any given point on a map. Another method for representing fluid motion is a streamline. A streamline represents the path of a small volume of fluid as it flows. When the flow pattern changes with time, the...
11.9K
Turbulent Flow01:24

Turbulent Flow

905
Turbulent flow is characterized by unpredictable fluctuations in velocity and pressure, which result in a chaotic fluid movement distinct from the orderly patterns of laminar flow. While laminar flow is governed by smooth, parallel layers with minimal mixing, turbulent flow exhibits highly irregular, three-dimensional patterns. This behavior arises due to instabilities in the fluid's velocity profile, and amplifies as the flow velocity increases. Minor disturbances, known as turbulent...
905
Shock Waves01:16

Shock Waves

2.8K
While deriving the Doppler formula for the observed frequency of a sound wave, it is assumed that the speed of sound in the medium is greater than the source's speed through it. When this condition is breached, a shock wave occurs.
When the source's speed approaches the speed of sound, constructive interference between successive wavefronts emitted by the source occurs immediately behind it. Initially, scientists believed that this constructive interference would result in such high...
2.8K
Brain Waves01:23

Brain Waves

4.8K
Brain waves are electrical signals generated by the neurons in the brain, which are regularly monitored to measure mental activities. Brain waves and their frequency ranges can be measured using an electroencephalogram or EEG. There are four main types of brain waves, each with distinct characteristics:
4.8K
Travelling Waves01:04

Travelling Waves

7.5K
A wave is a disturbance that propagates from its source, repeating itself periodically, and is typically associated with simple harmonic motion. Mechanical waves are governed by Newton's laws and require a medium to travel. A medium is a substance in which a mechanical wave propagates, and the medium produces an elastic restoring force when it is deformed.
Water waves, sound waves, and seismic waves are some examples of mechanical waves. For water waves, the wave propagation medium is...
7.5K
Turbulent Flow: Problem Solving01:09

Turbulent Flow: Problem Solving

586
Carbonation is a process used to dissolve carbon dioxide gas in a liquid, commonly used in the production of carbonated beverages. Achieving efficient carbonation requires careful control of temperature, pressure, and flow conditions. By adjusting these parameters, carbonation efficiency can be maximized, producing a higher concentration of CO2 in the liquid.
Temperature is a key factor in CO2 solubility. In this case, the CO2 gas and the liquid are cooled to 20°C. Lower temperatures enhance...
586

You might also read

Related Articles

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

Sort by
Same author

Cortical dynamics of neural-connectivity fields.

Journal of computational neuroscience·2025
Same author

A cortical field theory - dynamics and symmetries.

Journal of computational neuroscience·2024
Same author

Noise induced quiescence of epileptic spike generation in patients with epilepsy.

Journal of computational neuroscience·2021
Same author

Mechanism of visual network dysfunction in relapsing-remitting multiple sclerosis and its relation to cognition.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology·2019
Same author

Towards a Neuronal Gauge Theory.

PLoS biology·2016
Same author

Dynamic causal modelling of electrographic seizure activity using Bayesian belief updating.

NeuroImage·2015
Same journal

Learning under constraints: a theoretical framework for comparing resource-constrained learning in biological and artificial systems.

Frontiers in computational neuroscience·2026
Same journal

MsGCN: a multi-stream graph convolutional network for multiband PLV graph fusion in EEG-based biometric identification.

Frontiers in computational neuroscience·2026
Same journal

AI-driven neuroanalytic modeling for mental health: multichannel CNN-based autism spectrum disorder detection via facial pattern analysis.

Frontiers in computational neuroscience·2026
Same journal

Modeling multiscale neural dynamics for EEG-based emotion recognition using an attentive wavelet-transformer framework.

Frontiers in computational neuroscience·2026
Same journal

New directions for complex systems in contemporary neuroscience: a morphodynamic and emergent function approach.

Frontiers in computational neuroscience·2026
Same journal

NMDA receptor kinetics drive distinct routes to chaotic firing in pyramidal neurons.

Frontiers in computational neuroscience·2026
See all related articles

Related Experiment Video

Updated: Apr 7, 2026

Measurements of Waves in a Wind-wave Tank Under Steady and Time-varying Wind Forcing
08:54

Measurements of Waves in a Wind-wave Tank Under Steady and Time-varying Wind Forcing

Published on: February 13, 2018

9.2K

Wave turbulence and cortical dynamics.

Gerald K Cooray1,2

  • 1Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.

Frontiers in Computational Neuroscience
|April 6, 2026
PubMed
Summary
This summary is machine-generated.

Brain activity exhibits turbulent dynamics, similar to wave turbulence. This study models neural fields using kinetic equations, explaining spectral patterns and offering a unified framework for brain activity analysis.

Keywords:
cortical tissueneural fieldsself organized criticalityspectral dynamicsturbulent flow

More Related Videos

Disruption of Frontal Lobe Neural Synchrony During Cognitive Control by Alcohol Intoxication
09:26

Disruption of Frontal Lobe Neural Synchrony During Cognitive Control by Alcohol Intoxication

Published on: February 6, 2019

22.4K
Using Wavelet Entropy to Demonstrate how Mindfulness Practice Increases Coordination between Irregular Cerebral and Cardiac Activities
08:08

Using Wavelet Entropy to Demonstrate how Mindfulness Practice Increases Coordination between Irregular Cerebral and Cardiac Activities

Published on: May 10, 2017

15.4K

Related Experiment Videos

Last Updated: Apr 7, 2026

Measurements of Waves in a Wind-wave Tank Under Steady and Time-varying Wind Forcing
08:54

Measurements of Waves in a Wind-wave Tank Under Steady and Time-varying Wind Forcing

Published on: February 13, 2018

9.2K
Disruption of Frontal Lobe Neural Synchrony During Cognitive Control by Alcohol Intoxication
09:26

Disruption of Frontal Lobe Neural Synchrony During Cognitive Control by Alcohol Intoxication

Published on: February 6, 2019

22.4K
Using Wavelet Entropy to Demonstrate how Mindfulness Practice Increases Coordination between Irregular Cerebral and Cardiac Activities
08:08

Using Wavelet Entropy to Demonstrate how Mindfulness Practice Increases Coordination between Irregular Cerebral and Cardiac Activities

Published on: May 10, 2017

15.4K

Area of Science:

  • Neuroscience
  • Physics
  • Complex Systems

Background:

  • Cortical activity (EEG/MEG) shows complex dynamics across scales.
  • Spectral analysis reveals power-law behavior, characteristic of turbulent systems.

Purpose of the Study:

  • Derive a kinetic equation for neural field activity using wave turbulence theory.
  • Investigate how nonlinear interactions shape spectral features in brain activity.
  • Provide a unifying framework for interpreting large-scale brain dynamics.

Main Methods:

  • Applied wave turbulence theory to derive a kinetic equation for neural fields.
  • Analyzed energy and pseudo-particle density flow in k-space via cascades.
  • Explored the impact of 3-wave and 4-wave nonlinear interactions on spectral properties.

Main Results:

  • Neural field activity exhibits energy and pseudo-particle density flow through k-space cascades.
  • Nonlinear interactions influence spectral features like harmonic generation and dispersion.
  • Observed power-law decays in empirical data align with turbulent cascade models.

Conclusions:

  • Cortical dynamics show features consistent with turbulent wave systems.
  • Both single and dual cascades, along with mixed 3- and 4-wave interactions, are implicated.
  • A turbulence-based framework provides a principled approach to understanding brain activity, including state transitions and seizures.