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

Theoretical Approaches to Psychological Disorder01:29

Theoretical Approaches to Psychological Disorder

857
The development of psychological disorders, which are characterized by deviant, maladaptive, and personally distressing behaviors, has been explored through several theoretical approaches.
Biological approach
The biological approach posits that internal, organic factors are the primary causes of such disorders. This perspective emphasizes brain structure and function, genetic predispositions, and neurotransmitter imbalances. For example, schizophrenia has been associated with both genetic...
857
Depressive Disorders: Etiology01:27

Depressive Disorders: Etiology

498
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...
498
Graphs of Functions01:30

Graphs of Functions

337
Graphs of functions provide a visual representation of how output values change in response to varying inputs. Each point on the graph corresponds to an ordered pair, where the x-coordinate (independent variable) determines the horizontal position and the y-coordinate (dependent variable) determines the vertical position. Linear functions like y = x give a straight line, indicating a constant rate of change.Nonlinear functions display more complex behaviors. Even power functions generate...
337
Major Hormones and Their Functions01:27

Major Hormones and Their Functions

1.9K
Hormones, the biochemical messengers produced by endocrine glands, are pivotal in regulating bodily functions and maintaining homeostasis. Each hormone's balance is crucial; imbalances can lead to significant physiological disruptions. Major hormones include oxytocin, cortisol, epinephrine, estrogen, testosterone, thyroxine, growth hormone, insulin, and glucagon.
Oxytocin, produced in the hypothalamus and released by the pituitary gland, plays a role in social bonding, childbirth, and...
1.9K
Depressive Disorders: MDD and Dysthymia01:27

Depressive Disorders: MDD and Dysthymia

781
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...
781
Graphs of Trigonometric Functions01:29

Graphs of Trigonometric Functions

377
Trigonometric functions exhibit periodic and symmetrical behavior, deeply rooted in the unit circle. The sine and cosine functions correspond to the vertical and horizontal projections, respectively, of a point rotating counterclockwise around the circle. These functions trace smooth, repeating waveforms with identical periods and bounded ranges. The tangent function is defined as the ratio of sine to cosine and produces an unbounded curve that repeats every units, with vertical asymptotes...
377

You might also read

Related Articles

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

Sort by
Same author

Transcriptomic Identification of Diagnostic Biomarkers for Alcohol-Associated Liver Cirrhosis: Integration of Population-Level Epidemiology with Multi-Cohort Transcriptomic Analysis.

International journal of molecular sciences·2026
Same author

Lag-adjusted functional network connectivity reveals sensorimotor and higher cognitive network alterations in depression.

Research square·2026
Same author

Multisite Chronic Pain Reveals Neuro-Immune-Metabolic Dysregulation across Rheumatoid Arthritis and Depression.

Research (Washington, D.C.)·2026
Same author

Putamen function and MAOA genotype define genetic and neural subtypes of hyperactivity-impulsivity in ADHD.

Journal of affective disorders·2026
Same author

Measuring the Impacts of Urbanicity and Different Exposome Factors on Human Brain through Exposure Network Mapping.

Neuroscience bulletin·2026
Same author

Multimodal fusion of brain imaging and proteomics reveals a brain-body pathway linking depression and metabolic dysfunction.

Psychological medicine·2026

Related Experiment Video

Updated: Feb 2, 2026

MRI-guided dmPFC-rTMS as a Treatment for Treatment-resistant Major Depressive Disorder
08:20

MRI-guided dmPFC-rTMS as a Treatment for Treatment-resistant Major Depressive Disorder

Published on: August 11, 2015

14.6K

Abnormal Dynamic Functional Network Connectivity and Graph Theoretical Analysis in Major Depressive Disorder.

Dongmei Zhi, Xiaohong Ma, Luxian Lv

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |November 17, 2018
    PubMed
    Summary

    Major depressive disorder (MDD) is linked to altered dynamic functional brain connectivity. MDD patients exhibit distinct network states, spending more time in a weakly-connected state associated with self-focused thinking.

    More Related Videos

    Author Spotlight: Unveiling the Connection Between Sleep Disorders and Cognitive Symptoms in Depression
    04:33

    Author Spotlight: Unveiling the Connection Between Sleep Disorders and Cognitive Symptoms in Depression

    Published on: April 26, 2024

    1.5K
    Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy
    12:09

    Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy

    Published on: August 5, 2014

    18.5K

    Related Experiment Videos

    Last Updated: Feb 2, 2026

    MRI-guided dmPFC-rTMS as a Treatment for Treatment-resistant Major Depressive Disorder
    08:20

    MRI-guided dmPFC-rTMS as a Treatment for Treatment-resistant Major Depressive Disorder

    Published on: August 11, 2015

    14.6K
    Author Spotlight: Unveiling the Connection Between Sleep Disorders and Cognitive Symptoms in Depression
    04:33

    Author Spotlight: Unveiling the Connection Between Sleep Disorders and Cognitive Symptoms in Depression

    Published on: April 26, 2024

    1.5K
    Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy
    12:09

    Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy

    Published on: August 5, 2014

    18.5K

    Area of Science:

    • Neuroscience
    • Psychiatry
    • Network Science

    Background:

    • Major depressive disorder (MDD) is a prevalent mood disorder.
    • Previous research focused on static functional connectivity in MDD.
    • Dynamic functional network connectivity (dFNC) offers a novel perspective.

    Purpose of the Study:

    • To investigate disrupted topological organization of dFNC in MDD using graph theory.
    • To explore differences in dynamic brain network states between MDD patients and healthy controls.
    • To correlate dFNC abnormalities with symptom severity and cognitive function.

    Main Methods:

    • Utilized resting-state fMRI data from 182 MDD patients and 218 healthy controls.
    • Applied Group Information Guided Independent Component Analysis (GIG-ICA) and sliding window analysis.
    • Employed k-means clustering to identify dynamic functional states and analyzed network properties.

    Main Results:

    • Identified five distinct dynamic functional states, with three showing significant group differences in occurrence.
    • MDD patients spent more time in a weakly-connected state associated with self-focused thinking.
    • Observed abnormal functional network connectivity (FNC) between prefrontal, sensorimotor, and cerebellum networks, with increased node efficiency in MDD.

    Conclusions:

    • This study provides novel evidence of aberrant time-varying brain activity in Chinese MDD patients.
    • Disrupted dynamic functional network connectivity may underlie impaired cognitive functions in MDD.
    • Findings highlight the importance of dynamic network analysis for understanding MDD pathophysiology.