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 Control of Respiration01:18

Neural Control of Respiration

The neural regulation of respiration is a meticulously coordinated process primarily controlled by the respiratory centers located within the brainstem. These centers, composed of specialized neurons, transmit nerve impulses that control the contraction and relaxation of our respiratory muscles.
Respiratory Centers in the Brainstem
Two primary areas comprise the respiratory center: the medullary respiratory center in the medulla oblongata and the pontine respiratory group in the pons. The...
Physiology of Respiration II: Neurogenic Control of Respiration01:22

Physiology of Respiration II: Neurogenic Control of Respiration

The neurogenic control of respiration coordinates various neural networks and pathways to regulate breathing rate and depth, meeting the body's oxygen and carbon dioxide exchange requirements. This system adapts to physiological and environmental conditions, ensuring optimal breathing patterns.
Central Control
The brainstem is the primary site of central control, hosting respiratory centers:
Physiological Control of Respiration01:23

Physiological Control of Respiration

Introduction
Breathing, a seemingly passive process, is regulated by the respiratory center in the brainstem. This center coordinates the involuntary control of respirations, which means it occurs without conscious effort, ensuring a smooth and uninterrupted pattern.
Regulation of Ventilation
The body maintains ventilation by monitoring levels of carbon dioxide (CO2), oxygen (O2), and hydrogen ion concentration (pH) in the arterial blood. Among these factors, the level of CO2 plays a crucial...
Mechanism of Breathing II: Expiration01:23

Mechanism of Breathing II: Expiration

The Physiology of Expiration: A Seamless Respiratory Process
Expiration, or exhaling, is a complex physiological process that begins as the inspiratory muscles begin to relax. This relaxation triggers a series of events that epitomize the efficiency of the respiratory system.
Mechanism of Expiration:
Mechanism of Breathing I: Inspiration01:30

Mechanism of Breathing I: Inspiration

Introduction to Inspiration: The Respiratory System in Action
The respiratory system, an essential network for breathing, comprises the conducting and respiratory zones, each playing a crucial role in the overall process of respiration. Let us explore the detailed mechanism of inspiration, or inhalation, which is the first phase of the respiratory cycle.
Pathway of Air during Inspiration
During inspiration, air enters our body through the nose or mouth and moves through the conducting zone,...
Mechanism of Breathing III: The Accessory Muscles01:21

Mechanism of Breathing III: The Accessory Muscles

The Role of Accessory Muscles in the Respiratory System
The respiratory system is a complex network that relies on primary respiratory muscles like the diaphragm, but also involves accessory muscles to enhance lung expansion and airflow during both inhalation and exhalation.
Enhancing Inhalation with Accessory Muscles:
Accessory muscles such as the sternocleidomastoid, scalene, intercostal, and abdominal muscles are crucial when additional respiratory effort is required, such as during deep...

You might also read

Related Articles

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

Sort by
Same author

When Can Brain Connectivity Track the Working Mind? A Large-Scale Benchmark of Dynamic Functional Connectivity Across Cognitive Paradigms.

bioRxiv : the preprint server for biology·2026
Same author

Beta bursts spatiotemporal profiles and their links to hemodynamic responses during movement and rest.

Imaging neuroscience (Cambridge, Mass.)·2026
Same author

Frequency-Specific tACS Differentially Modulates Cortical Oscillations and Motor Performance.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society·2026
Same author

Global signal regression reduces connectivity patterns related to physiological signals and does not alter EEG-derived connectivity.

Frontiers in neuroimaging·2025
Same author

Investigating the Variability of Physiological Response Functions across Individuals and Brain Regions in Functional Magnetic Resonance Imaging.

Brain topography·2025
Same author

Influence of systemic low-frequency oscillations on fMRI identifiability -Implications for denoising and fingerprinting.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025

Related Experiment Video

Updated: Jun 18, 2026

Software for Analysis of Heart Rate and Blood Pressure Time-series Data from the Valsalva Maneuver
14:28

Software for Analysis of Heart Rate and Blood Pressure Time-series Data from the Valsalva Maneuver

Published on: June 27, 2025

Nonlinear, data-driven modeling of cardiorespiratory control mechanisms.

Georgios D Mitsis1

  • 1Department of Electrical and Computer Engineering, University of Cyprus, Nicosia 1678, Cyprus. gmisis@ucy.ac.cy

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|December 8, 2009
PubMed
Summary

New algorithms for data-driven nonlinear systems identification reveal insights into cardiovascular and respiratory control. These methods leverage spontaneous physiological variability for non-invasive analysis of complex bodily systems.

More Related Videos

Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction
09:20

Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction

Published on: February 13, 2021

Acquisition and Semi-Automated Analysis of Respiratory Muscle Surface Electromyography
09:42

Acquisition and Semi-Automated Analysis of Respiratory Muscle Surface Electromyography

Published on: January 24, 2025

Related Experiment Videos

Last Updated: Jun 18, 2026

Software for Analysis of Heart Rate and Blood Pressure Time-series Data from the Valsalva Maneuver
14:28

Software for Analysis of Heart Rate and Blood Pressure Time-series Data from the Valsalva Maneuver

Published on: June 27, 2025

Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction
09:20

Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction

Published on: February 13, 2021

Acquisition and Semi-Automated Analysis of Respiratory Muscle Surface Electromyography
09:42

Acquisition and Semi-Automated Analysis of Respiratory Muscle Surface Electromyography

Published on: January 24, 2025

Area of Science:

  • Physiology
  • Systems Biology
  • Computational Biology

Background:

  • Cardiovascular and respiratory systems exhibit complex, nonlinear dynamics.
  • Understanding these control mechanisms is crucial for diagnosing and treating various medical conditions.
  • Traditional modeling approaches often require strong prior assumptions about system structure.

Purpose of the Study:

  • To apply novel data-driven nonlinear systems identification algorithms to study integrated cardiovascular and respiratory control.
  • To investigate cerebrovascular regulation and respiratory control using experimental data.
  • To demonstrate the utility of these methods for analyzing complex physiological systems.

Main Methods:

  • Utilized recently developed data-driven nonlinear systems identification algorithms.
  • Applied algorithms to experimental data from resting conditions, orthostatic stress, and autonomic blockade.
  • Analyzed respiratory control during remifentanil infusion in a closed-loop system.
  • Leveraged spontaneous physiological variability for non-invasive analysis.

Main Results:

  • Successfully modeled cerebrovascular regulation and respiratory control mechanisms.
  • Demonstrated the effectiveness of data-driven approaches for complex physiological systems.
  • Showcased the potential of spontaneous physiological variability for extracting functional information.
  • Identified practical challenges including nonstationarities and model order selection.

Conclusions:

  • Data-driven nonlinear systems identification offers a powerful, assumption-free approach to modeling physiological systems.
  • Spontaneous physiological variability is a rich, non-invasively obtainable source of information for systems-level analysis.
  • Further research is needed to address practical issues for widespread clinical application.