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

Protein Networks02:26

Protein Networks

4.6K
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,...
4.6K
Protein Networks02:26

Protein Networks

2.9K
2.9K
Network Covalent Solids02:18

Network Covalent Solids

16.2K
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...
16.2K
Structural Organization of the Human Body: An Overview01:18

Structural Organization of the Human Body: An Overview

29.5K
It is convenient to consider the body's structures in terms of fundamental levels of organization that increase in complexity: subatomic particles, atoms, molecules, organelles, cells, tissues, organs, organ systems, and organisms.
To study the chemical level of organization, scientists consider the simplest building blocks of matter: subatomic particles, atoms, and molecules. All matter in the universe is composed of one or more unique pure substances called elements, familiar examples of...
29.5K
Chromosome Structure02:40

Chromosome Structure

26.6K
A functional eukaryotic chromosome must contain three elements: a centromere, telomeres, and numerous origins of replication.
The centromere is a DNA sequence that links sister chromatids. This is also where kinetochores, protein complexes to which spindle microtubules attach, are constructed after the chromosome is replicated. The kinetochores allow the spindle microtubules to move the chromosomes within the cell during cell division.
Telomeres consist of non-coding repetitive nucleotide...
26.6K
Construction of Root Locus01:15

Construction of Root Locus

419
The construction of a root locus involves several key steps to analyze and visualize the behavior of a system's poles with varying gain. The number of branches in the root locus equals the number of closed-loop poles and is symmetrical about the real axis.
For positive gain values, the root locus exists on the real axis to the left of an odd number of finite open-loop poles or zeros. The root locus starts at the open-loop poles and traces the paths of the closed-loop poles as the gain...
419

You might also read

Related Articles

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

Sort by
Same author

White matter reflects the childhood exposome.

bioRxiv : the preprint server for biology·2026
Same author

Neural Control of Autonomic Arousal During Threat Anticipation Revealed by High-Resolution Cardiac Contractility.

bioRxiv : the preprint server for biology·2026
Same author

Incentive valence differentially engages open- and closed-loop basal ganglia circuits during movement initiation.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

The PMADS Project: A Longitudinal Multimodal Cohort Study to Understand Risk for Perinatal Mood and Anxiety Disorders.

bioRxiv : the preprint server for biology·2026
Same author

Highly replicable multisite patterns of adolescent white matter maturation.

bioRxiv : the preprint server for biology·2026
Same author

Mapping developmental patterns of intrinsic timescale.

bioRxiv : the preprint server for biology·2026
Same journal

Cortical similarity networks in the rat brain: Postnatal development and sensitivity to early life stress.

Network neuroscience (Cambridge, Mass.)·2026
Same journal

Increased sensitivity in identifying language-related functional connectivity using jackknife resampling analyses.

Network neuroscience (Cambridge, Mass.)·2026
Same journal

Phase-dependent stimulation response is shaped by the brain's dynamic functional connectivity.

Network neuroscience (Cambridge, Mass.)·2026
Same journal

Restoring oscillatory dynamics in Alzheimer's disease: A laminar whole-brain model of serotonergic psychedelic effects.

Network neuroscience (Cambridge, Mass.)·2026
Same journal

Distributed cortical network dynamics of binocular convergent eye movements in humans.

Network neuroscience (Cambridge, Mass.)·2026
Same journal

High-resolution Bayesian Virtual Epileptic Patient using neural field models.

Network neuroscience (Cambridge, Mass.)·2026
See all related articles

Related Experiment Video

Updated: Feb 6, 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

1.6K

Sensitivity analysis of human brain structural network construction.

Kuang Wei1,2, Matthew Cieslak3, Clint Greene4

  • 1Department of Physics, University of Chicago, Chicago, IL, USA.

Network Neuroscience (Cambridge, Mass.)
|August 10, 2018
PubMed
Summary
This summary is machine-generated.

Understanding brain connectivity requires careful selection of diffusion MRI tractography parameters. This study guides researchers in optimizing parameters to avoid disconnected network models and accurately interpret structural brain networks.

Keywords:
Brain networksConnectomicsHuman Connectome ProjectTractographyWhite matter connectivity

More Related Videos

Three-Dimensional Shape Modeling and Analysis of Brain Structures
05:33

Three-Dimensional Shape Modeling and Analysis of Brain Structures

Published on: November 14, 2019

7.6K
Construction of Local Field Potential Microelectrodes for in vivo Recordings from Multiple Brain Structures Simultaneously
06:07

Construction of Local Field Potential Microelectrodes for in vivo Recordings from Multiple Brain Structures Simultaneously

Published on: March 14, 2022

3.8K

Related Experiment Videos

Last Updated: Feb 6, 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

1.6K
Three-Dimensional Shape Modeling and Analysis of Brain Structures
05:33

Three-Dimensional Shape Modeling and Analysis of Brain Structures

Published on: November 14, 2019

7.6K
Construction of Local Field Potential Microelectrodes for in vivo Recordings from Multiple Brain Structures Simultaneously
06:07

Construction of Local Field Potential Microelectrodes for in vivo Recordings from Multiple Brain Structures Simultaneously

Published on: March 14, 2022

3.8K

Area of Science:

  • Neuroscience
  • Medical Imaging
  • Network Science

Background:

  • Network neuroscience uses diffusion MRI and tractography to map human brain structural connectivity.
  • Current understanding of how tractography parameters influence structural network construction is limited.

Purpose of the Study:

  • To investigate the impact of varying tractography parameters on structural brain network models.
  • To provide guidelines for optimizing parameter selection in network neuroscience research.

Main Methods:

  • Utilized diffusion images from the Human Connectome Project (HCP).
  • Analyzed effects of atlas spatial resolution, streamline count, and grey matter dilation on network metrics.
  • Evaluated graph metrics and subject ranks across different parameter combinations.

Main Results:

  • Injudicious parameter choices (e.g., fine atlases with few streamlines) can create disconnected network models.
  • Developed methods to mitigate the generation of disconnected networks.
  • Individual subject ranks in graph metric distributions vary with atlas scale.

Conclusions:

  • Optimizing tractography parameters is crucial for accurate structural network analysis.
  • Atlas parcellation schemes significantly influence the interpretation of brain network characteristics.
  • This work provides a framework for robust network neuroscience studies.