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

Weighted Mean00:57

Weighted Mean

While taking the arithmetic, geometric, or harmonic mean of a sample data set, equal importance is assigned to all the data points. However, all the values may not always be equally important in some data sets. An intrinsic bias might make it more important to give more weightage to specific values over others.
For example, consider the number of goals scored in the matches of a tournament. While computing the average number of goals scored in the tournament, it may be more important to...
Assessment of Diffusion and Perfusion01:17

Assessment of Diffusion and Perfusion

Understanding and evaluating diffusion and perfusion is critical in assessing a patient's respiratory and circulatory health. These processes play key roles in maintaining the body's internal environment, ensuring that tissues receive adequate oxygen while waste products are efficiently removed.
The Role of Diffusion in Respiration
Diffusion is the process by which molecules move from an area of higher concentration to an area of lower concentration. In the respiratory system, this principle...
Protein Networks02:26

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
Protein Networks02:26

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...

You might also read

Related Articles

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

Sort by
Same author

Resilience of precuneus neurotrophic signaling pathways despite amyloid pathology in prodromal Alzheimer's disease.

Biological psychiatry·2014
Same author

Magnetoacoustic tomography with magnetic induction for high-resolution bioimepedance imaging through vector source reconstruction under the static field of MRI magnet.

Medical physics·2014
Same author

Hollow superparamagnetic PLGA/Fe3O4 composite microspheres for lysozyme adsorption.

Nanotechnology·2014
Same author

[A bird's eye view of the algorithms and software packages for reconstructing phylogenetic trees].

Dong wu xue yan jiu = Zoological research·2014
Same author

Functional and biodegradable dendritic macromolecules with controlled architectures as nontoxic and efficient nanoscale gene vectors.

Biotechnology advances·2014
Same author

[Effects of artificial vegetation on the spatial heterogeneity of soil moisture and salt in coastal saline land of Chongming Dongtan, Shanghai].

Ying yong sheng tai xue bao = The journal of applied ecology·2014

Related Experiment Video

Updated: May 17, 2026

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

A weighted small world network measure for assessing functional connectivity.

Marcos Bolaños1, Edward M Bernat, Bin He

  • 1Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI 48824, USA.

Journal of Neuroscience Methods
|October 23, 2012
PubMed
Summary
This summary is machine-generated.

This study introduces novel graph theoretic measures for analyzing brain connectivity, improving upon existing methods for complex network analysis. These new measures offer enhanced accuracy in characterizing functional brain networks and their dynamics.

More Related Videos

Electroencephalography Network Indices as Biomarkers of Upper Limb Impairment in Chronic Stroke
06:37

Electroencephalography Network Indices as Biomarkers of Upper Limb Impairment in Chronic Stroke

Published on: July 14, 2023

Soft Pneumatic Robot Modulates Graph Theory Metrics of Brain Network for Hand Rehabilitation After Stroke
05:30

Soft Pneumatic Robot Modulates Graph Theory Metrics of Brain Network for Hand Rehabilitation After Stroke

Published on: October 10, 2025

Related Experiment Videos

Last Updated: May 17, 2026

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

Electroencephalography Network Indices as Biomarkers of Upper Limb Impairment in Chronic Stroke
06:37

Electroencephalography Network Indices as Biomarkers of Upper Limb Impairment in Chronic Stroke

Published on: July 14, 2023

Soft Pneumatic Robot Modulates Graph Theory Metrics of Brain Network for Hand Rehabilitation After Stroke
05:30

Soft Pneumatic Robot Modulates Graph Theory Metrics of Brain Network for Hand Rehabilitation After Stroke

Published on: October 10, 2025

Area of Science:

  • Neuroscience
  • Network Science
  • Computational Biology

Background:

  • Characterizing complex functional connectivity in the brain is crucial.
  • Graph theoretic measures are valuable for analyzing multivariate connectivity in neural networks.
  • Existing methods for weighted graphs have limitations in precision.

Purpose of the Study:

  • To propose new small-world graph theoretic measures for brain connectivity analysis.
  • To enhance the calculation of weighted graph measures using an improved bivariate measure.
  • To assess the performance of these new measures on diverse datasets.

Main Methods:

  • Developed new weighted graph theoretic measures (clustering coefficient and path length).
  • Utilized a novel bivariate time-frequency phase-synchrony (TFPS) measure for improved signal analysis.
  • Applied the new measures to Zachary's Karate Club social network and event-related potential (ERP) data.

Main Results:

  • The proposed graph theoretic measures demonstrated superior performance compared to previous weighted graph measures.
  • The new measures yielded expected and reliable results for both the social network and ERP datasets.
  • The TFPS measure improved the isolation of relevant neural activity.

Conclusions:

  • The novel graph theoretic measures offer a more accurate and robust approach to analyzing brain functional connectivity.
  • These advancements in network analysis can better characterize dynamic interactions within neuronal oscillations.
  • The findings support the utility of these measures in neuroscience and cognitive control research.