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

Time and frequency -Domain Interpretation of Phase-lead Control01:24

Time and frequency -Domain Interpretation of Phase-lead Control

570
Phase-lead controllers are commonly used in various control systems to enhance response speed and stability. Adjusting the brightness on a television screen offers a practical example of phase-lead control. When contrast is enhanced, a phase-lead controller is employed. Mathematically, phase-lead control is identified when the first parameter is smaller than the second.
The design of phase-lead control involves the strategic placement of poles and zeros to balance steady-state error and system...
570
Time and frequency -Domain Interpretation of Phase-lag Control01:21

Time and frequency -Domain Interpretation of Phase-lag Control

475
Phase-lag controllers are widely used in control systems to improve stability and reduce steady-state errors. A dimmer switch controlling the brightness of a light bulb serves as a practical example of phase-lag control, gradually adjusting the bulb's brightness. Mathematically, phase-lag control or low-pass filtering is represented when the factor 'a' is less than 1.
Phase-lag controllers do not place a pole at zero, but instead influence the steady-state error by amplifying any...
475
Phase-lead and Phase-lag Controllers01:22

Phase-lead and Phase-lag Controllers

668
Understanding the working function of different types of controllers can be illustrated with practical analogies, such as adjusting a stereo's volume equalizer. Cranking up the bass involves a phase-lead controller, which functions as a high-pass filter, while increasing the treble uses a phase-lag controller, which acts as a low-pass filter. PD controllers, similar to high-pass filters, enhance the system's response to high-frequency components. PI controllers, akin to low-pass...
668
Interference: Path Lengths01:10

Interference: Path Lengths

2.5K
Consider two sources of sound, that may or may not be in phase, emitting waves at a single frequency, and consider the frequencies to be the same.
Two special sources may be considered when they are in phase. This can be easily achieved by feeding the two sources from the same source. An example would be synchronizing the two speakers by feeding them with the same source, such as the sound waves produced by a tuning fork. This setup ensures that the two sources have the same frequency and are...
2.5K
Phase Changes01:19

Phase Changes

3.7K
Phase transitions play an important theoretical and practical role in the study of heat flow. In melting or fusion, a solid turns into a liquid; the opposite process is freezing. In evaporation, a liquid turns into a gas; the opposite process is condensation.
A substance melts or freezes at a temperature called its melting point and boils or condenses at its boiling point. These temperatures depend on pressure. High pressure favors the denser form of the substance, so typically, high pressure...
3.7K
Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

460
Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
460

You might also read

Related Articles

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

Sort by
Same author

Unobtrusive Yet Precise Velocity Perturbations During Voluntary Elbow Movement for Reliable Joint Dynamics Assessment.

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

Continuous volitional control of a bionic leg supports diverse walking patterns in both agonist-antagonist muscle interface and bone-anchored prosthesis users.

PNAS nexus·2026
Same author

From subthalamic local field potentials to the selection of chronic deep brain stimulation contacts in Parkinson's disease - A systematic review.

Brain stimulation·2025
Same author

Versatile kinematics-based constraint identification applied to robot task reproduction.

Frontiers in robotics and AI·2025
Same author

AI in therapeutic and assistive exoskeletons and exosuits: Influences on performance and autonomy.

Science robotics·2025
Same author

System Performance Analysis of the Shoulder Elbow Perturbator.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings]·2025

Related Experiment Video

Updated: May 5, 2026

Author Spotlight: Unlocking New Insights in fNIRS Studies - A Novel Framework for Inter-Brain Synchrony Analysis
05:59

Author Spotlight: Unlocking New Insights in fNIRS Studies - A Novel Framework for Inter-Brain Synchrony Analysis

Published on: October 6, 2023

3.5K

Face to phase: pitfalls in time delay estimation from coherency phase.

S Floor Campfens1, Herman van der Kooij, Alfred C Schouten

  • 1Laboratory of Biomechanical Engineering, MIRA Institute of Biomedical Engineering and Technical Medicine, University of Twente, PO box 217, 7500 AE, Enschede, the Netherlands, s.f.campfens@utwente.nl.

Journal of Computational Neuroscience
|November 19, 2013
PubMed
Summary
This summary is machine-generated.

Estimating neural transmission delays using corticomuscular coherency can be misleading due to sensory feedback. Bidirectional interactions and feedback loops significantly affect time delay estimations, rendering some methods unreliable.

More Related Videos

Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method
08:42

Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method

Published on: September 3, 2021

3.0K
Combined Invasive Subcortical and Non-invasive Surface Neurophysiological Recordings for the Assessment of Cognitive and Emotional Functions in Humans
08:25

Combined Invasive Subcortical and Non-invasive Surface Neurophysiological Recordings for the Assessment of Cognitive and Emotional Functions in Humans

Published on: May 19, 2016

10.5K

Related Experiment Videos

Last Updated: May 5, 2026

Author Spotlight: Unlocking New Insights in fNIRS Studies - A Novel Framework for Inter-Brain Synchrony Analysis
05:59

Author Spotlight: Unlocking New Insights in fNIRS Studies - A Novel Framework for Inter-Brain Synchrony Analysis

Published on: October 6, 2023

3.5K
Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method
08:42

Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method

Published on: September 3, 2021

3.0K
Combined Invasive Subcortical and Non-invasive Surface Neurophysiological Recordings for the Assessment of Cognitive and Emotional Functions in Humans
08:25

Combined Invasive Subcortical and Non-invasive Surface Neurophysiological Recordings for the Assessment of Cognitive and Emotional Functions in Humans

Published on: May 19, 2016

10.5K

Area of Science:

  • Neuroscience
  • Systems Neuroscience
  • Computational Neuroscience

Background:

  • Corticomuscular coherency phase is commonly used to estimate neural transmission delays.
  • However, experimental estimates often conflict with physiological expectations.
  • Recent studies highlight the influence of sensory feedback and bidirectional neural interactions.

Purpose of the Study:

  • To investigate the impact of bidirectional interactions on time delay estimations from corticomuscular coherency.
  • To evaluate the effects on Directed Transfer Function (DTF) and Partial Directed Coherence (PDC).

Main Methods:

  • A feedback model of the corticomuscular system was developed.
  • The model simulated efferent and afferent pathway strengths and sensory feedback.
  • The accuracy of coherency phase, DTF phase, and PDC phase was assessed.

Main Results:

  • The model reproduced experimentally observed time delay ranges by adjusting pathway strengths and feedback.
  • Sensory feedback and closed-loop systems caused underestimation of transmission delays with coherency and DTF.
  • Partial Directed Coherence (PDC) phase accurately estimated efferent transmission delays across all simulations.

Conclusions:

  • Corticomuscular coherency and DTF phase are unreliable for estimating transmission delays in neural systems with sensory feedback.
  • These methods can yield meaningless time delay estimates in the presence of feedback loops.
  • PDC is a more robust measure for estimating efferent transmission delays in complex neural circuits.