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

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,...
Depressive Disorders: Etiology01:27

Depressive Disorders: Etiology

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...
Long-term Depression01:05

Long-term Depression

Long-term depression, or LTD, is one of the ways by which synaptic plasticity—changes in the strength of chemical synapses—can occur in the brain. LTD is the process of synaptic weakening that occurs over time between pre and postsynaptic neuronal connections. The synaptic weakening of LTD works in opposition to synaptic strengthening by long-term potentiation (LTP) and together are the main mechanisms that underlie learning and memory.
Long-term Depression01:03

Long-term Depression

Long-term depression, or LTD, is one of the ways by which synaptic plasticity—changes in the strength of chemical synapses—can occur in the brain. LTD is the process of synaptic weakening that occurs over time between pre and postsynaptic neuronal connections. The synaptic weakening of LTD works in opposition to synaptic strengthening by long-term potentiation (LTP) and together are the main mechanisms that underlie learning and memory.
Calcium Ion Concentration Mechanism
If over time, all...
Depressive Disorders: MDD and Dysthymia01:27

Depressive Disorders: MDD and Dysthymia

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...
G-protein Coupled Receptors01:21

G-protein Coupled Receptors

G-protein coupled receptors are ligand binding receptors that indirectly affect changes in the cell. The actual receptor is a single polypeptide that transverses the cell membrane seven times creating intracellular and extracellular loops. The extracellular loops create a ligand specific pocket which binds to neurotransmitters or hormones. The intracellular loops holds onto the G-protein.

You might also read

Related Articles

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

Sort by
Same author

Developmental predictors of suicide attempts from childhood to early adulthood: a 15-year prospective cohort study.

Lancet regional health. Americas·2026
Same author

Trans-ancestry genome-wide association meta-analysis of antidepressant response to selective serotonin reuptake inhibitors in clinical studies of depression.

medRxiv : the preprint server for health sciences·2026
Same author

The association between body mass index and treatment outcomes in major depressive disorder: a CAN-BIND-1 study.

Journal of psychiatric research·2026
Same author

The conceptualization, measurement, and critical appraisal of computational models of anhedonia in depression.

Neuroscience and biobehavioral reviews·2026
Same author

The centrality of mood symptoms in bipolar disorder: A systematic review of network analysis studies.

Trends in psychiatry and psychotherapy·2026
Same author

In Vitro Investigation of the PneumoWave Biosensor for the Identification of Central Sleep Apnea in Pediatrics.

Biosensors·2026
Same journal

The longitudinal relationship between co-rumination and depressive symptoms in adolescents: A systematic review and meta-analytic structural equation modeling.

Journal of affective disorders·2026
Same journal

Child-experienced discrimination and parent mental health in Latino families.

Journal of affective disorders·2026
Same journal

Suicide risk prediction and analysis of associated factors among high school students in four provinces of China based on explainable machine learning.

Journal of affective disorders·2026
Same journal

Integrating hypertriglyceridemia, inflammation, and β-cell stress in clozapine- and olanzapine-associated pancreatitis.

Journal of affective disorders·2026
Same journal

Exploring the functioning trajectories and associated factors in adolescents with first-diagnosis major depressive disorder: Evidence from the sBEAD cohort.

Journal of affective disorders·2026
Same journal

Effects of a self-directed cognitive behavioral therapy manual on depressive symptoms among youths incarcerated for drug-related offenses.

Journal of affective disorders·2026
See all related articles

Related Experiment Video

Updated: May 16, 2026

Animal Models of Depression - Chronic Despair Model (CDM)
05:47

Animal Models of Depression - Chronic Despair Model (CDM)

Published on: September 23, 2021

Acoustics of depression.

Sri Harsha Dumpala1, Katerina Dikaios2, Ross Langley3

  • 1Nova Scotia Health Authority, Halifax, Nova Scotia, Canada; Dalhousie University, Department of Psychiatry, Halifax, Nova Scotia, Canada.

Journal of Affective Disorders
|May 14, 2026
PubMed
Summary
This summary is machine-generated.

Objective depression measurement is possible using speech audio. Acoustic and prosodic speech features accurately differentiate depression severity in diagnosed patients, showing potential for clinical application.

Keywords:
Acoustic features of speechDepressive symptom severityMachine learningMajor depressive disorderSpeech analysis

More Related Videos

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

A New Method for Inducing a Depression-Like Behavior in Rats
07:57

A New Method for Inducing a Depression-Like Behavior in Rats

Published on: February 22, 2018

Related Experiment Videos

Last Updated: May 16, 2026

Animal Models of Depression - Chronic Despair Model (CDM)
05:47

Animal Models of Depression - Chronic Despair Model (CDM)

Published on: September 23, 2021

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

A New Method for Inducing a Depression-Like Behavior in Rats
07:57

A New Method for Inducing a Depression-Like Behavior in Rats

Published on: February 22, 2018

Area of Science:

  • Speech analysis
  • Computational psychiatry
  • Machine learning in healthcare

Background:

  • Speech reflects mood, enabling objective depression measurement from audio.
  • Previous studies lacked diagnosed participants and comprehensive acoustic feature analysis.
  • The specific acoustic features for clinically relevant depression remain unclear.

Purpose of the Study:

  • To identify which acoustic features of speech can objectively measure clinically relevant depression severity.
  • To develop and validate machine learning models for depression severity detection using speech.
  • To explore the utility of a wide range of acoustic features, including prosodic and system-level characteristics.

Main Methods:

  • Analyzed 77 acoustic features (system, source, spectral, prosodic) in 239 adults (147 with major depressive disorder).
  • Used XGBoost machine learning models trained on speech data from neutral, positive, and negative prompts.
  • Validated models on an unseen test set to differentiate depression severity (none, mild, moderate, severe) using the Montgomery Åsberg Depression Rating Scale (MADRS).

Main Results:

  • Prosodic features were the most informative for discriminating depression severity.
  • Speech energy velocity, intensity variation, voiced rate, pause duration, and third formant variance consistently predicted depression severity.
  • Intensity, energy, pause duration, and harmonic difference were key features in the XGBoost models for severity discrimination.

Conclusions:

  • Acoustic, particularly prosodic, features can effectively discriminate clinically relevant depression levels in diagnosed individuals.
  • The identified speech predictors of depression are robust across different emotional contexts.
  • These findings suggest a potential for applying speech analysis in diverse clinical settings for depression assessment.