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

Organization of the Brain01:30

Organization of the Brain

The brain is an integral component of the nervous system and serves as the center for processing sensory inputs, making decisions, and directing bodily actions. This complex organ is organized into three primary sections: the hindbrain, midbrain, and forebrain, each responsible for a range of vital functions.
Hindbrain
The hindbrain, located at the base of the brain, plays a vital role in regulating automatic processes that sustain life. It includes the medulla oblongata, which is essential for...

You might also read

Related Articles

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

Sort by
Same author

Keying Into Cognition: Temporal Smoothing of Smartphone Typing Behaviors for Passive Assessment of Processing Speed and Executive Function in Individuals With Mood Disorders.

Cognitive computation·2026
Same author

Instantaneous Frequency: A New Functional Biomarker for Dynamic Brain Causal Networks.

AI in neuroscience·2025
Same author

A simple platelet biomarker is associated with symptom severity in major depressive disorder.

Molecular psychiatry·2025
Same author

A comprehensive survey of complex brain network representation.

Meta-radiology·2025
Same author

TGNet: tensor-based graph convolutional networks for multimodal brain network analysis.

BioData mining·2024
Same author

Using a Novel Digital Go/No-Go to Dissociate Intra-subject Temporal Fluctuations in Reaction Time and Accuracy.

medRxiv : the preprint server for health sciences·2024
Same journal

LiftReg: Limited Angle 2D/3D Deformable Registration.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention·2026
Same journal

Inverse Consistency by Construction for Multistep Deep Registration.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention·2026
Same journal

Can Crowdsourced Annotations Improve AI-based Congestion Scoring For Bedside Lung Ultrasound?

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention·2026
Same journal

Equivariant Filters for Efficient Tracking in 3D Imaging.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention·2026
Same journal

Lobar Lung Density Embeddings with a Transformer encoder (LobTe) to predict emphysema progression in COPD.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention·2026
Same journal

uniGradICON: A Foundation Model for Medical Image Registration.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention·2026
See all related articles

Related Experiment Video

Updated: May 15, 2026

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
08:51

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms

Published on: November 1, 2019

A framework for quantifying node-level community structure group differences in brain connectivity networks.

Johnson J GadElkarim1, Dan Schonfeld, Olusola Ajilore

  • 1Electrical and Computer Engineering Department, University of Illinois at Chicago, USA. jgadel2@uic.edu

Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
|January 5, 2013
PubMed
Summary
This summary is machine-generated.

This study introduces a new method to analyze brain network communities in major depression. It found significant differences in brain network structures, particularly in the default mode network, linked to rumination.

More Related Videos

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance
09:01

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance

Published on: May 7, 2014

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

Related Experiment Videos

Last Updated: May 15, 2026

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
08:51

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms

Published on: November 1, 2019

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance
09:01

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance

Published on: May 7, 2014

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

Area of Science:

  • Neuroscience
  • Network Science
  • Computational Psychiatry

Background:

  • Understanding brain network alterations in major depressive disorder (MDD) is crucial for diagnosis and treatment.
  • Previous studies suggest disruptions in brain connectivity and community structure in MDD.
  • Node-level community structure analysis offers a novel perspective on brain organization.

Purpose of the Study:

  • To develop and validate a framework for quantifying node-level community structures in anatomical brain networks.
  • To identify differences in brain community structures between individuals with MDD and healthy controls.
  • To investigate the role of the default mode network in MDD.

Main Methods:

  • Constructed hierarchical binary trees using diffusion tensor imaging (DTI)-tractography derived brain networks.
  • Employed modularity (Q) and a novel path length difference metric to define communities.
  • Developed a statistical framework to detect local differences in community structures between groups.
  • Applied the framework to a cohort of 42 MDD patients and 47 healthy controls.

Main Results:

  • Identified significant differences in node-level community structures between MDD patients and controls.
  • Observed alterations in several nodes within the default mode network (DMN).
  • Specifically, the bilateral precuneus showed significant group differences, a region implicated in self-awareness.

Conclusions:

  • The proposed framework effectively quantifies node-level community structure differences in brain networks.
  • Findings suggest altered brain network organization in the DMN of individuals with MDD.
  • These network differences may underlie the increased ruminative self-reflection characteristic of depression.