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

Protein Networks

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 Networks

Protein Networks

Network Covalent Solids

Network Covalent Solids

Network covalent solids contain a three-dimensional network of covalently bonded atoms as found in the crystal structures of nonmetals like diamond, graphite, silicon, and some covalent compounds, such as silicon dioxide (sand) and silicon carbide (carborundum, the abrasive on sandpaper). Many minerals have networks of covalent bonds.
To break or to melt a covalent network solid, covalent bonds must be broken. Because covalent bonds are relatively strong, covalent network solids are typically...

Cluster Sampling Method

Cluster Sampling Method

Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...

Vesicular Tubular Clusters

Vesicular Tubular Clusters

After budding out from the ER membrane, some COPII vesicles lose their coat and fuse with one another to form larger vesicles and interconnected tubules called vesicular tubular clusters or VTCs. These clusters constitute a compartment at the ER-Golgi interface known as ERGIC (Endoplasmic Reticulum Golgi Intermediate Compartment). The ERGIC is a mobile membrane-bound cargo transport system that sorts proteins secreted from ER and delivers them to the Golgi.
With the help of motor proteins such...

Network Function of a Circuit

Network Function of a Circuit

Frequency response analysis in electrical circuits provides vital insights into a circuit's behavior as the frequency of the input signal changes. The transfer function, a mathematical tool, is instrumental in understanding this behavior. It defines the relationship between phasor output and input and comes in four types: voltage gain, current gain, transfer impedance, and transfer admittance. The critical components of the transfer function are the poles and zeros.

You might also read

Related Articles

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

Sort by

Same author

EEG-Pype: An accessible MNE-Python pipeline with graphical user interface for preprocessing and analysis of resting-state electroencephalography data.

PLoS computational biology·2026

Same author

Replication and validation of two novel magnetoencephalography functional connectivity measures in Alzheimer's disease.

Imaging neuroscience (Cambridge, Mass.)·2026

Same author

Building blocks of functional connectivity measures for aperiodic electrophysiological brain signals.

Neuroimage. Reports·2025

Same author

An Interactive Brain Atlas of Knowledge.

bioRxiv : the preprint server for biology·2025

Same author

Biomarkers.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2025

Same author

The Virtual Brain Ontology: A Digital Knowledge Framework for Reproducible Brain Network Modeling.

bioRxiv : the preprint server for biology·2025

Search research articles

Related Experiment Video

Updated: Feb 2, 2026

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

Published on: October 19, 2021

Brain network clustering with information flow motifs.

Marcus Märtens¹, Jil Meier¹, Arjan Hillebrand²

¹1Delft University of Technology, Faculty of Electrical Engineering, Mathematics and Computer Science, P.O Box 5031, Delft, The Netherlands.

Applied Network Science

|November 17, 2018

Summary

This summary is machine-generated.

The bi-directional two-hop path is key for brain information flow across frequencies. Network analysis reveals frequency-dependent brain region subdivisions based on this motif.

Keywords:

Brain networks Effective connectivity Information flow Network clustering Network motifs

More Related Videos

CRISPR Gene Editing Tool for MicroRNA Cluster Network Analysis

CRISPR Gene Editing Tool for MicroRNA Cluster Network Analysis

Published on: April 25, 2022

Modeling the Functional Network for Spatial Navigation in the Human Brain

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

Related Experiment Videos

Last Updated: Feb 2, 2026

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

Published on: October 19, 2021

CRISPR Gene Editing Tool for MicroRNA Cluster Network Analysis

CRISPR Gene Editing Tool for MicroRNA Cluster Network Analysis

Published on: April 25, 2022

Modeling the Functional Network for Spatial Navigation in the Human Brain

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

Area of Science:

Neuroscience
Network Science
Brain Imaging

Background:

Global information flow patterns in the human brain have been identified using magnetoencephalography (MEG) network analysis.
The specific subgraph properties dominating functional brain networks at different frequency bands remain largely unknown.
Network motifs, fundamental building blocks of networks, are implicated in healthy and abnormal brain function.

Purpose of the Study:

To investigate the dominant network motifs in functional brain networks across different frequency bands.
To identify the small-scale subgraph properties that characterize information flow at various frequencies.
To explore the relationship between network motifs and brain region organization.

Main Methods:

Developed a novel network construction method to analyze motifs within different frequency bands of MEG data.
Applied network analysis techniques to identify and quantify the prevalence of various motifs.
Utilized motif-based clustering to reveal subdivisions within functional brain networks.

Main Results:

Identified the bi-directional two-hop path as the most significant motif for information flow in functional brain networks.
Demonstrated that the dominance of this motif varies across different frequency bands.
Clustering based on the bi-directional two-hop path revealed spatially coherent, frequency-dependent subdivisions involving posterior, occipital, and frontal brain regions.

Conclusions:

The bi-directional two-hop path is a critical motif underlying information flow in the human brain's functional networks.
Functional brain organization exhibits frequency-dependent characteristics, with distinct subdivisions emerging at different frequency bands.
This motif-based approach provides new insights into the frequency-specific organization and dynamics of the human brain.