Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Depression: Overview

Depression: Overview

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,...

You might also read

Related Articles

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

Sort by

Same author

Association of lipid profiles with suicide attempts in young adults with first-episode drug-naive major depressive disorder: a gender-specific analysis.

Scientific reports·2026

Same author

The cGAS-STING pathway contributes to cisplatin-induced skeletal muscle atrophy through altered proteostasis and myogenic signaling.

Cell communication and signaling : CCS·2026

Same author

Single-Cell and Integrative Analyses Uncover Therapeutic Potential of RFX1-Mediated Cuproptosis in PitNETs.

Journal of integrative neuroscience·2026

Same author

Development of KASP molecular markers and fingerprinting based on reduced representation genome sequencing of garlic.

Frontiers in plant science·2026

Same author

Sex-specific temporal-lobe functional connectivity alterations in early-onset bipolar disorder.

Cerebral cortex (New York, N.Y. : 1991)·2026

Same author

Ampere-Level Syngas Synthesis by Controllable Active Hydrogen Supply to Regulate CO<sub>2</sub> Reduction Depth on High-Entropy (CuZnAlZrCe)O<sub>2</sub> Oxide Nanosheets.

Angewandte Chemie (International ed. in English)·2026

Search research articles

Related Experiment Video

Updated: Aug 30, 2025

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

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

Published on: July 7, 2023

Machine learning approaches for diagnosing depression using EEG: A review.

Yuan Liu¹, Changqin Pu², Shan Xia¹

¹Department of Psychosomatic Medicine, The First Affiliated Hospital of Nanchang University, No.17 Yongwaizheng Street, Donghu District, Nanchang 330006, Jiangxi Province, China.

Translational Neuroscience

|September 1, 2022

Summary

Diagnosing depression is challenging due to behavioral methods. Machine learning (ML) with electroencephalography offers a promising, objective approach to improve depression screening and diagnosis.

Keywords:

EEG artificial intelligence identification psychiatric disorder

More Related Videos

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

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

Published on: April 26, 2024

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms

Published on: November 1, 2019

Related Experiment Videos

Last Updated: Aug 30, 2025

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

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

Published on: July 7, 2023

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

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

Published on: April 26, 2024

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms

Published on: November 1, 2019

Area of Science:

Neuroscience
Computational Psychiatry
Medical Diagnostics

Background:

Depression is a major global public health concern affecting over 300 million individuals worldwide.
Current clinical diagnosis of depression relies on subjective behavioral methods, lacking objective laboratory criteria.
This diagnostic gap hinders accurate identification and timely intervention for depression.

Purpose of the Study:

To explore the potential of computational psychiatry and machine learning (ML) in improving depression diagnosis.
To investigate the use of resting-state electroencephalography (EEG) combined with ML for objective depression screening.
To highlight the need for continuous improvement of ML models for enhanced diagnostic accuracy.

Main Methods:

Utilizing resting-state electroencephalography (EEG) data.
Applying machine learning (ML) algorithms for predictive modeling.
Analyzing EEG patterns for objective diagnostic markers.

Main Results:

Machine learning models show promise in alleviating the diagnosis of depression.
Combining EEG with ML offers a data-driven approach to complement behavioral diagnostics.
Existing ML models require further refinement for optimal performance in depression screening.

Conclusions:

Objective diagnostic criteria for depression are needed, moving beyond traditional behavioral assessments.
Resting-state EEG and ML represent a significant advancement in computational psychiatry for depression diagnosis.
Continued development of ML prediction models is crucial for improving depression screening and potential application to other psychiatric disorders.