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

Depressive Disorders: MDD and Dysthymia01:27

Depressive Disorders: MDD and Dysthymia

261
Depressive disorders are a group of mental health conditions characterized by pervasive feelings of sadness, diminished pleasure in life, and a significant impact on daily functioning. These conditions are most prevalent in individuals during their 30s and affect women at twice the rate of men. Contrary to popular belief, younger individuals are generally more susceptible to these disorders than older adults. Two key types of depressive disorders include Major Depressive Disorder (MDD) and...
261
Brain Imaging01:14

Brain Imaging

419
Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans),  magnetic resonance imaging (MRI),  functional magnetic resonance imaging (fMRI), and Transcranial Magnetic...
419
Depressive Disorders: Etiology01:27

Depressive Disorders: Etiology

197
Depressive disorders result from a complex interplay of biological, psychological, and sociocultural factors, each contributing uniquely to the development and persistence of the condition. Understanding these factors provides critical insight into the multifaceted nature of depression.
Biological Factors in Depression
Biological predispositions significantly influence the risk of developing depressive disorders. Genetic studies highlight the role of variations in the serotonin transporter...
197

You might also read

Related Articles

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

Sort by
Same author

Quantifying Similarity of Dynamic Brain Networks: Two Novel Indices for Structural Change and Temporal Evolution.

Bioengineering (Basel, Switzerland)·2025
Same author

Modulation of High-Frequency rTMS on Reward Circuitry in Individuals with Nicotine Dependence: A Preliminary fMRI Study.

Neural plasticity·2024
Same author

Magnetic resonance temperature imaging of laser-induced thermotherapy using proton resonance frequency shift: evaluation of different sequences in phantom and porcine brain at 7 T.

Japanese journal of radiology·2022
Same author

A novel fully immersive virtual reality environment for upper extremity rehabilitation in patients with stroke.

Annals of the New York Academy of Sciences·2021
Same author

Proactive Motor Functional Recovery Following Immersive Virtual Reality-Based Limb Mirroring Therapy in Patients with Subacute Stroke.

Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics·2020
Same author

Psychosocial risk factors and outcomes associated with suicide attempts in childhood: A retrospective study.

Journal of psychiatric research·2020

Related Experiment Video

Updated: Oct 26, 2025

Developing Neuroimaging Phenotypes of the Default Mode Network in PTSD: Integrating the Resting State, Working Memory, and Structural Connectivity
10:43

Developing Neuroimaging Phenotypes of the Default Mode Network in PTSD: Integrating the Resting State, Working Memory, and Structural Connectivity

Published on: July 1, 2014

15.4K

Diffusion tensor imaging brain structural clustering patterns in major depressive disorder.

Dongrong Xu1, Guojun Xu1,2, Zhiyong Zhao1,2

  • 1Department of Psychiatry, Columbia University & Molecular Imaging and Neuropathology Division, New York State Psychiatric Institute, New York, New York, USA.

Human Brain Mapping
|July 27, 2021
PubMed
Summary
This summary is machine-generated.

Major depressive disorder (MDD) shows altered brain network patterns, particularly in early stages. These network abnormalities may normalize over time, suggesting brain plasticity may play a role in recovery.

Keywords:
brain networking patterndiffusion tensor imagingmajor depressive disorder

More Related Videos

Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging
12:21

Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging

Published on: September 12, 2011

25.4K
Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
09:33

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

Published on: July 28, 2013

28.7K

Related Experiment Videos

Last Updated: Oct 26, 2025

Developing Neuroimaging Phenotypes of the Default Mode Network in PTSD: Integrating the Resting State, Working Memory, and Structural Connectivity
10:43

Developing Neuroimaging Phenotypes of the Default Mode Network in PTSD: Integrating the Resting State, Working Memory, and Structural Connectivity

Published on: July 1, 2014

15.4K
Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging
12:21

Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging

Published on: September 12, 2011

25.4K
Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
09:33

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

Published on: July 28, 2013

28.7K

Area of Science:

  • Neuroscience
  • Psychiatry
  • Medical Imaging

Background:

  • Major depressive disorder (MDD) is a complex mental health condition with unclear neurological underpinnings.
  • Brain network alterations are increasingly recognized as potential biomarkers in MDD.
  • The impact of disease duration on these network patterns remains incompletely understood.

Purpose of the Study:

  • To investigate differences in brain network indices between patients with MDD and healthy controls (HCs).
  • To examine how disease duration influences these network patterns in MDD.
  • To explore the potential role of brain plasticity in network alterations.

Main Methods:

  • Magnetic resonance diffusion tensor imaging (DTI) data from 45 MDD patients and 41 HCs were analyzed.
  • Network indices were calculated using the 246-region Brainnetome Atlas.
  • MDD patients were subgrouped by disease duration (short-term MDD [MDDS] and long-term MDD [MDDL]).
  • Correlation analyses examined the relationship between network indices and illness duration.

Main Results:

  • Significant differences in network indices were found between the MDDS group and HCs, but not between the overall MDD and HC groups.
  • MDDS exhibited higher clustering coefficients (CC) in the precentral and caudal lingual gyri compared to HCs.
  • MDDL showed higher CC in the postcentral gyrus and dorsal granular insula (right hemisphere).
  • Network resilience analysis indicated more randomized networks in the MDDS group.
  • Disease duration correlated with network alterations in the caudal and rostral lingual gyri.

Conclusions:

  • The duration of illness significantly impacts brain networking patterns in MDD.
  • Network abnormalities in MDD may be masked by clinical heterogeneity, especially when considering subgroups.
  • Brain plasticity might contribute to the normalization of network patterns in long-term MDD, suggesting a potential recovery effect.