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

Functional Brain Systems: Reticular Formation01:13

Functional Brain Systems: Reticular Formation

3.4K
The reticular formation is a complex network of gray and white matter located within the brainstem extending from the medulla to the midbrain.
Within the reticular formation, there are several distinct nuclei that can be classified into three broad categories. The Raphe nuclei are located along the midline of the brainstem. They are primarily known for their role in synthesizing and releasing serotonin, a neurotransmitter involved in regulating mood, appetite, sleep, and circadian rhythms. The...
3.4K

You might also read

Related Articles

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

Sort by
Same author

Safety of high-dose dual therapy for <i>Helicobacter pylori</i> eradication in patients with varying degrees of metabolic associated fatty liver disease.

Frontiers in pharmacology·2026
Same author

<i>Helicobacter pylori</i> and metabolic-associated fatty liver disease severity: a meta-analysis.

Frontiers in medicine·2026
Same author

A novel JAK1 mutation identified in a patient with severe atopic dermatitis phenotype: Mechanistic insights and IL-4Rα targeted therapy.

Clinical immunology (Orlando, Fla.)·2026
Same author

Combined Analysis of Bulk and Single-Cell Transcriptomic Data Reveals Dormancy-Associated Genes in Colorectal Cancer.

International journal of molecular sciences·2026
Same author

Tumor cells metabolically resist immune-checkpoint therapy by macrophage efferocytosis-mediated fatty acid recycling.

Cancer cell·2026
Same author

Expanding the cofactor range of aldehyde reductase YqhD by mutating key amino acids.

Biotechnology letters·2026

Related Experiment Video

Updated: Nov 27, 2025

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy
11:15

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy

Published on: June 27, 2013

34.1K

Construction and Application of Functional Brain Network Based on Entropy.

Lingyun Zhang1, Taorong Qiu1, Zhiqiang Lin1

  • 1Department of Computer, Nanchang University, Nanchang 330029, China.

Entropy (Basel, Switzerland)
|December 8, 2020
PubMed
Summary

Functional brain network (FBN) construction using electroencephalogram (EEG) signals can identify fatigue driving. Fuzzy entropy-based FBN models show superior accuracy and stability in detecting driver fatigue.

Keywords:
fatigue drivingfunctional brain networkfuzzy entropy

More Related Videos

Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

1.4K
Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy
12:09

Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy

Published on: August 5, 2014

18.3K

Related Experiment Videos

Last Updated: Nov 27, 2025

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy
11:15

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy

Published on: June 27, 2013

34.1K
Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

1.4K
Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy
12:09

Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy

Published on: August 5, 2014

18.3K

Area of Science:

  • Neuroscience
  • Signal Processing
  • Biomedical Engineering

Background:

  • Functional brain networks (FBNs) represent dynamic neural interactions and brain network properties.
  • Characterizing FBNs accurately from electroencephalogram (EEG) signals, especially in fatigue driving, remains challenging.
  • Entropy measures complexity and uncertainty in EEG signals, offering potential for FBN construction.

Purpose of the Study:

  • To investigate entropy-based methods for constructing Functional Brain Networks (FBNs) from EEG data.
  • To evaluate the effectiveness of different entropy features in characterizing EEG signals for fatigue driving detection.
  • To develop and validate an FBN model for accurately identifying fatigue driving states.

Main Methods:

  • Selection of appropriate entropy features to characterize EEG signals.
  • Construction of FBN models using selected entropy features.
  • Application of FBN models to a real-world dataset of fatigue driving.
  • Analysis of network measurement indicators for classification performance.

Main Results:

  • FBN models based on various entropy measures were constructed and compared for fatigue driving identification.
  • The FBN model utilizing fuzzy entropy demonstrated excellent classification recognition rates and good stability.
  • The fuzzy entropy-based FBN model achieved higher accuracy and stability compared to other models, even with varying EEG signal lengths.

Conclusions:

  • Fuzzy entropy is a suitable feature for constructing robust Functional Brain Networks from EEG data.
  • Entropy-based FBNs provide an effective approach for detecting fatigue driving states.
  • The proposed method offers a promising tool for monitoring driver fatigue and enhancing road safety.