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

Depression: Overview01:18

Depression: Overview

405
Depression is a prevalent mental illness marked by persistent sadness and lack of interest in previously enjoyable activities. It can take several forms, including major depression, persistent depressive disorder, and bipolar I and II disorders. Symptoms range from emotional changes like chronic worry to physical changes like sleep disturbances and suicidal thoughts. From a neurobiological perspective, depression is believed to be triggered by abnormalities in the brain's prefrontal cortex,...
405
Brain Imaging01:14

Brain Imaging

337
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...
337
Depressive Disorders: Etiology01:27

Depressive Disorders: Etiology

178
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...
178

You might also read

Related Articles

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

Sort by
Same author

[A generalizable epilepsy detection network based on dual-attention mechanism].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi·2026
Same author

Hybrid Probabilistic Information Set and Multi-Criteria Group Decision-Making Approach: A Case Study to Evaluate Urban Flood Resilience.

Entropy (Basel, Switzerland)·2026
Same author

Glycine Receptor α2 Mediates Vasodilation via Endothelial eNOS Signaling.

Circulation research·2026
Same author

Factors influencing nurses' knowledge on peripherally inserted central catheter care in Guizhou, China: A web-based cross-sectional study.

Scientific reports·2026
Same author

Commentary on "Incident subclinical vertebral fractures and health-related quality of life: JPOS cohort study".

Journal of bone and mineral metabolism·2026
Same author

A Successful Monitoring of a Pregnant Woman Suffering from Mixed Connective Tissue Disease-Associated Interstitial Lung Disease: A Case Report.

International journal of women's health·2026
Same journal

[Advances in research on neuroelectrophysiological characteristics of post-stroke cognitive impairment based on quantitative electroencephalography and acupuncture interventions].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi·2026
Same journal

[Mechanisms and applications of magnesium ion-regulated stem cell functions in promoting tendon-bone interface healing].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi·2026
Same journal

[Applications and challenges of ultra-high molecular weight polyethylene fibers in minimally invasive medical devices].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi·2026
Same journal

[Research on auditory neurofeedback technology and its multi-disciplinary applications].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi·2026
Same journal

[Application and perspective of novel auditory intervention paradigms based on verbal and nonverbal stimuli for severe traumatic brain injury].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi·2026
Same journal

[Research progress on the neuromodulation targets in stroke rehabilitation].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi·2026
See all related articles

Related Experiment Video

Updated: Oct 1, 2025

Individualized rTMS Treatment for Depression using an fMRI-Based Targeting Method
07:12

Individualized rTMS Treatment for Depression using an fMRI-Based Targeting Method

Published on: August 2, 2021

3.7K

[Research on depression recognition based on brain function network].

Bingtao Zhang1,2,3, Wenying Zhou2,3, Yanlin Li3,4

  • 1School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070, P. R. China.

Sheng Wu Yi Xue Gong Cheng Xue Za Zhi = Journal of Biomedical Engineering = Shengwu Yixue Gongchengxue Zazhi
|March 1, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a novel brain function network (BFN) framework using electroencephalogram (EEG) data to identify depression. The method reveals significant topological alterations in the brain networks of depressed individuals, achieving up to 94.11% recognition accuracy.

Keywords:
Brain function networkDepressionPhase lag indexResting state electroencephalogram

More Related Videos

Author Spotlight: Therapeutic Benefit of Closed-Loop Deep Brain Stimulation in Depression Treatment
05:19

Author Spotlight: Therapeutic Benefit of Closed-Loop Deep Brain Stimulation in Depression Treatment

Published on: July 7, 2023

2.6K
Design and Implementation of an fMRI Study Examining Thought Suppression in Young Women with, and At-risk, for Depression
08:42

Design and Implementation of an fMRI Study Examining Thought Suppression in Young Women with, and At-risk, for Depression

Published on: May 19, 2015

10.9K

Related Experiment Videos

Last Updated: Oct 1, 2025

Individualized rTMS Treatment for Depression using an fMRI-Based Targeting Method
07:12

Individualized rTMS Treatment for Depression using an fMRI-Based Targeting Method

Published on: August 2, 2021

3.7K
Author Spotlight: Therapeutic Benefit of Closed-Loop Deep Brain Stimulation in Depression Treatment
05:19

Author Spotlight: Therapeutic Benefit of Closed-Loop Deep Brain Stimulation in Depression Treatment

Published on: July 7, 2023

2.6K
Design and Implementation of an fMRI Study Examining Thought Suppression in Young Women with, and At-risk, for Depression
08:42

Design and Implementation of an fMRI Study Examining Thought Suppression in Young Women with, and At-risk, for Depression

Published on: May 19, 2015

10.9K

Area of Science:

  • Neuroscience
  • Computational Psychiatry
  • Biomedical Engineering

Background:

  • Traditional electroencephalogram (EEG) studies for depression often overlook inter-electrode correlations, hindering the detection of abnormal brain topology.
  • Existing methods struggle to capture the complex functional connectivity alterations characteristic of depression.

Purpose of the Study:

  • To propose a novel framework for depression recognition using brain function networks (BFNs) derived from EEG.
  • To identify potential biomarkers for depression by analyzing BFN topological properties.
  • To investigate alterations in information processing ability in patients with depression.

Main Methods:

  • Constructed BFNs using the phase lag index to mitigate volume conductor effects.
  • Selected BFN indexes related to "small world" properties and minimum spanning tree characteristics from both weighted and binary networks.
  • Employed a progressive index analysis strategy to identify potential depression biomarkers.
  • Utilized resting-state EEG data from 48 subjects for validation.

Main Results:

  • Significant changes in inter-group synchronization were observed in the left temporal, right parietal occipital, and right frontal regions.
  • Weighted BFN indexes (shortest path length, clustering coefficient) and binary BFN indexes (leaf scores, diameter) correlated with the Patient Health Questionnaire-9 (PHQ-9) scores.
  • Achieved a highest depression recognition rate of 94.11%.
  • Demonstrated significantly reduced information processing ability in depressed patients compared to healthy controls.

Conclusions:

  • The proposed BFN framework offers a new approach for analyzing brain connectivity in depression.
  • Identified specific BFN topological features as potential biomarkers for depression recognition.
  • Highlights reduced information processing capacity as a key characteristic of depression.