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

Second Order systems I01:20

Second Order systems I

A servo system exemplifies a second-order system, featuring a proportional controller and load elements that ensure the output position aligns with the input position. The relationship between these components is described by a second-order differential equation. Applying the Laplace transform under zero initial conditions yields the transfer function, showing how inputs are converted to outputs in the system.
By reinterpreting the system, one can derive the closed-loop transfer function, which...
Second Order systems II01:18

Second Order systems II

In an underdamped second-order system, where the damping ratio ζ is between 0 and 1, a unit-step input results in a transfer function that, when transformed using the inverse Laplace method, reveals the output response. The output exhibits a damped sinusoidal oscillation, and the difference between the input and output is termed the error signal. This error signal also demonstrates damped oscillatory behavior. Eventually, as the system reaches a steady state, the error diminishes to zero.
If  ζ...
Anatomy of the Brain: Ventricles01:18

Anatomy of the Brain: Ventricles

There are hollow fluid-filled cavities known as ventricles deep inside the human brain. There are two lateral ventricles, one in each cerebral hemisphere, and each has three different projections — the anterior, inferior, and posterior horns visible from the lateral side. A thin membrane called the septum pellucidum separates the two lateral ventricles. The slender third ventricle in the diencephalon is connected to each lateral ventricle via a channel called the interventricular foramen. The...
Cerebral Edema l: Introduction01:19

Cerebral Edema l: Introduction

Cerebral edema is a pathological increase in brain water content that disrupts intracranial pressure regulation and impairs neurological function. Because the cranial vault is rigid, even modest increases in tissue volume can compromise cerebral perfusion, distort neural structures, and initiate secondary injury. Cerebral edema develops through four principal mechanisms: vasogenic, cytotoxic, interstitial, and ionic.Vasogenic EdemaVasogenic edema arises from disruption of the blood–brain...
Control Volume and System Representations01:16

Control Volume and System Representations

Two key frameworks are employed to analyze mass, energy, and momentum transfer: the control volume approach and the system approach. These frameworks offer different perspectives, depending on whether the focus is on a specific region in space (control volume approach) or a defined mass of fluid (system approach).
The control volume approach considers a stationary region in space through which fluid flows. This region is bounded by a control surface.  For instance, in the case of water flowing...
Cerebral Edema ll: Pathophysiology01:22

Cerebral Edema ll: Pathophysiology

Vasogenic edema is a major form of cerebral edema characterized by abnormal accumulation of fluid in the brain’s extracellular space due to disruption of the blood–brain barrier (BBB). The BBB is a specialized structure composed of endothelial cells connected by tight junctions, supported by astrocytic endfeet and a basement membrane. Under normal conditions, it tightly regulates the movement of ions, proteins, and solutes between the bloodstream and brain parenchyma. When this barrier loses...

You might also read

Related Articles

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

Sort by
Same author

The airborne transmission of viruses causes tight transmission bottlenecks.

Nature communications·2024
Same author

A psychrometric model to assess the biological decay of the SARS-CoV-2 virus in aerosols.

PeerJ·2021
Same author

Central venous pressure estimation from ultrasound assessment of the jugular venous pulse.

PloS one·2020
Same author

Upper-room ultraviolet air disinfection might help to reduce COVID-19 transmission in buildings: a feasibility study.

PeerJ·2020
Same author

Hidden dynamics of soccer leagues: The predictive 'power' of partial standings.

PloS one·2019
Same author

Overcoming the problem of multicollinearity in sports performance data: A novel application of partial least squares correlation analysis.

PloS one·2019

Related Experiment Video

Updated: Jun 4, 2026

Evaluation of Cerebral Blood Flow Autoregulation in the Rat Using Laser Doppler Flowmetry
07:12

Evaluation of Cerebral Blood Flow Autoregulation in the Rat Using Laser Doppler Flowmetry

Published on: January 19, 2020

Cerebral hydrodynamics are at a most a third order system.

Simon J Shepherd1, Clive B Beggs

  • 1Medical Biophysics Laboratory, University of Bradford, Richmond Road, Bradford BD7 1DP, UK.

Medical Hypotheses
|February 5, 2011
PubMed
Summary

The brain

Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Fluid Dynamics

Background:

  • The human brain utilizes a windkessel mechanism to regulate arterial pulse and ensure smooth cerebral blood flow.
  • Cerebrospinal fluid (CSF) dynamics are complex and not fully understood, impacting brain hydrodynamics.
  • Previous electrical analogue models of brain hydrodynamics have had limited success.

Purpose of the Study:

  • To investigate the order of the cerebral hydrodynamic system.
  • To determine the minimum model order required for accurately simulating brain hydrodynamics.
  • To advance the hypothesis that the cerebral system is at most a third-order system.

Main Methods:

  • Singular spectrum analysis (SSA) applied to arterial, venous, and CSF flow data.

More Related Videos

Assessing Cerebral Autoregulation via Oscillatory Lower Body Negative Pressure and Projection Pursuit Regression
11:26

Assessing Cerebral Autoregulation via Oscillatory Lower Body Negative Pressure and Projection Pursuit Regression

Published on: December 10, 2014

Systems Analysis of the Neuroinflammatory and Hemodynamic Response to Traumatic Brain Injury
07:21

Systems Analysis of the Neuroinflammatory and Hemodynamic Response to Traumatic Brain Injury

Published on: May 27, 2022

Related Experiment Videos

Last Updated: Jun 4, 2026

Evaluation of Cerebral Blood Flow Autoregulation in the Rat Using Laser Doppler Flowmetry
07:12

Evaluation of Cerebral Blood Flow Autoregulation in the Rat Using Laser Doppler Flowmetry

Published on: January 19, 2020

Assessing Cerebral Autoregulation via Oscillatory Lower Body Negative Pressure and Projection Pursuit Regression
11:26

Assessing Cerebral Autoregulation via Oscillatory Lower Body Negative Pressure and Projection Pursuit Regression

Published on: December 10, 2014

Systems Analysis of the Neuroinflammatory and Hemodynamic Response to Traumatic Brain Injury
07:21

Systems Analysis of the Neuroinflammatory and Hemodynamic Response to Traumatic Brain Injury

Published on: May 27, 2022

  • Computation of singular vectors to analyze spectral eigen-system of fluid flows.
  • Analysis of variance explained by successive singular vectors.
  • Main Results:

    • The first singular vector explained 67% of the observed variance in cerebral fluid flows.
    • The first two singular vectors collectively explained 96% of the variance.
    • The first three singular vectors accounted for over 99.5% of the observed variance.

    Conclusions:

    • The cerebral hydrodynamic system can be accurately modeled as a third-order system.
    • This finding provides a more precise framework for simulating brain hydrodynamics.
    • Understanding the system's order is crucial for successful hydrodynamic modeling.