Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Interference: Path Lengths

Interference: Path Lengths

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...

Electronic Distance Measuring Instruments

Electronic Distance Measuring Instruments

Electronic Distance Measuring Instruments (EDMs) are essential tools in modern surveying, offering precise distance measurements by emitting electromagnetic signals and calculating the time required for these signals to travel to a target and return. Two primary types of signals are used in EDMs — light waves and microwaves — each suited to specific environmental and distance requirements. Light-wave-based EDMs utilize either infrared or laser light, providing high accuracy over...

Distance Measurements by Taping

Distance Measurements by Taping

Tapes are essential in surveying for accurate, durable, and short-distance measurements. Made from lightweight, nylon-coated steel, they offer flexibility and strength for rugged outdoor use. The nylon coating protects against rust and wear, extending the tape's life. Standard lengths, around 30 meters, are marked in meters and millimeters for precision.Surveyors select tapes based on site conditions and accuracy needs. Lightweight, nylon-coated tapes are commonly used for ease of handling and...

Time and frequency -Domain Interpretation of Phase-lag Control

Time and frequency -Domain Interpretation of Phase-lag Control

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...

¹H NMR: Interpreting Distorted and Overlapping Signals

¹H NMR: Interpreting Distorted and Overlapping Signals

Spin systems where the difference in chemical shifts of the coupled nuclei is greater than ten times J are called first-order spin systems. These nuclei are weakly coupled, and their chemical shifts and coupling constant can generally be estimated from the well-separated signals in the spectrum.
As Δν decreases and the signals move closer, the doublets appear increasingly distorted. The intensities of the inner lines increase at the cost of those of the outer lines as the signals are...

Phase Contrast and Differential Interference Contrast Microscopy

Phase Contrast and Differential Interference Contrast Microscopy

Phase-Contrast Microscopes
In-phase-contrast microscopes, interference between light directly passing through a cell and light refracted by cellular components is used to create high-contrast, high-resolution images without staining. It is the oldest and simplest type of microscope that creates an image by altering the wavelengths of light rays passing through the specimen. Altered wavelength paths are created using an annular stop in the condenser. The annular stop produces a hollow cone of...

You might also read

Related Articles

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

Sort by

Same author

Vegetation-Atmosphere Water Deficit as the Primary Control on Alpine Steppe and Forest Coverage: An Empirical Assessment from the Altay Mountains, Northwestern China.

Biology·2026

Same author

Discriminating bipolar depression from major depressive disorder using functional and microstructural signatures of inferior fronto-occipital fasciculus: Promising results from an MRI study.

Journal of affective disorders·2026

Same author

Development of a prediction method for severe pancreatitis using a nomogram.

Frontiers in medicine·2026

Same author

Sex-specific alterations in the functional hierarchy of the insula in autism spectrum disorder and their associations with molecular profiles.

NeuroImage·2026

Same author

Thalamic atrophy and its impact on cognitive function in normal aging.

Brain research bulletin·2026

Same author

Impaired regional structure-function coupling as novel neurophenotype: mechanistic insights and diagnostic exploration in treatment-resistant depression.

Npj mental health research·2026

Search research articles

Related Experiment Video

Updated: Jan 16, 2026

Measurement of Quantum Interference in a Silicon Ring Resonator Photon Source

Measurement of Quantum Interference in a Silicon Ring Resonator Photon Source

Published on: April 4, 2017

Measuring phase-amplitude coupling using dispersion fuzzy mutual information.

Hao Zhang¹, Zhijie Bian², Xiaonan Guo¹

¹Hebei Key Laboratory of Information Transmission and Signal Processing, Yanshan University, Qinhuangdao 066004, China; School of Information Science and Engineering, Yan Shan University, Qinhuangdao 066004, China.

Computer Methods and Programs in Biomedicine

|September 25, 2025

Summary

This summary is machine-generated.

A new Dispersion Fuzzy Mutual Information (DFMI) method improves Phase-Amplitude Coupling (PAC) estimation in electroencephalography (EEG) signals for early Mild Cognitive Impairment (MCI) detection. DFMI offers better applicability and stable results compared to traditional methods.

Keywords:

Dispersion fuzzy mutual information Electroencephalography Mild cognitive impairment Phase-Amplitude coupling

More Related Videos

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping

Published on: March 20, 2017

Measurement of Coherence Decay in GaMnAs Using Femtosecond Four-wave Mixing

Measurement of Coherence Decay in GaMnAs Using Femtosecond Four-wave Mixing

Published on: December 3, 2013

Related Experiment Videos

Last Updated: Jan 16, 2026

Measurement of Quantum Interference in a Silicon Ring Resonator Photon Source

Measurement of Quantum Interference in a Silicon Ring Resonator Photon Source

Published on: April 4, 2017

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping

Published on: March 20, 2017

Measurement of Coherence Decay in GaMnAs Using Femtosecond Four-wave Mixing

Measurement of Coherence Decay in GaMnAs Using Femtosecond Four-wave Mixing

Published on: December 3, 2013

Area of Science:

Neuroscience
Biomedical Engineering
Signal Processing

Background:

Mild Cognitive Impairment (MCI) is an early stage of Alzheimer's disease (AD).
Electroencephalography (EEG) signals and Phase-Amplitude Coupling (PAC) are promising for MCI detection.
Existing PAC estimators have limitations in clinical application.

Purpose of the Study:

To propose and evaluate the Dispersion Fuzzy Mutual Information (DFMI) method as a novel PAC estimator.
To assess DFMI's applicability and performance compared to conventional PAC estimators.

Main Methods:

The DFMI method integrates dispersion entropy and mutual information for time series analysis.
It upgrades fuzzy entropy to a dual-channel algorithm, addressing pattern quantification challenges.
DFMI performance was evaluated via simulations, comparing sensitivity, data length dependency, noise, and artifact resistance.

Main Results:

DFMI effectively estimates PAC strength with reduced data length dependency and stable results.
The method demonstrated strong resistance to pseudo-trace signals and artifacts.
Analysis of MCI-EEG data revealed enhanced theta-gamma coupling and a shift in alpha-gamma coupling in MCI patients.

Conclusions:

DFMI is a viable PAC estimator for neural signals.
PAC alterations in MCI brains may present as coupling band attenuation.
DFMI shows potential for improved early diagnosis of MCI using EEG.