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

Facial Feedback Hypothesis01:24

Facial Feedback Hypothesis

305
Charles Darwin proposed that facial expressions are an evolutionary adaptation for communication. He argued that these expressions are not influenced by culture but are universal across species. For example, a snarling expression with exposed teeth signals a threat in many animals, including humans. Darwin also suggested that displaying an emotion can intensify the feeling. Smiling, for example, could enhance one's sense of happiness. This idea laid the foundation for understanding the role...
305
Channels of Non-Verbal Communication01:28

Channels of Non-Verbal Communication

45
Non-verbal communication plays a critical role in human interaction, influencing how individuals perceive emotions and psychological states. It operates through four primary channels: facial expressions, eye contact, body language, and touch. These non-verbal cues help convey meaning beyond spoken language and are often culturally influenced.Facial Expressions and Emotional RecognitionFacial expressions are among the most powerful and universal forms of non-verbal communication. Research has...
45
Non-Verbal Cues01:29

Non-Verbal Cues

37
Non-verbal communication extends beyond gestures and facial expressions to include vocal elements known as paralanguage. Paralanguage consists of non-verbal vocal cues such as pitch, loudness, speech rate, pauses, and non-verbal vocalizations like laughter, sighs, and moans. These elements not only accompany speech but also provide critical emotional and contextual information.The Role of Paralanguage in CommunicationParalanguage adds depth to spoken language by conveying emotions and...
37
Neuronal Communication01:28

Neuronal Communication

1.9K
Neurons, the fundamental units of the brain and nervous system, communicate through complex electrochemical signals that underpin all cognitive and bodily functions. This communication is primarily facilitated by a process involving the generation and propagation of an action potential along the axon of the neuron. When the internal electrical charge of a neuron surpasses a certain threshold, an action potential is triggered. This rapid change in voltage travels swiftly along the axon to the...
1.9K
Muscles for Facial Expressions01:14

Muscles for Facial Expressions

3.1K
The craniofacial muscles are a collection of approximately 20 thin skeletal muscles situated beneath the skin of the face and scalp. These muscles, primarily responsible for the vast array of human facial expressions, originate from the bones or fibrous structures of the skull and extend outwards to connect with the skin. While most skeletal muscles in the body are enveloped in thick fascia, facial muscles generally have a more delicate fascial covering, with the buccinator muscle being a...
3.1K
Therapeutic Communication01:30

Therapeutic Communication

5.9K
Communication is a lifelong learning process. Through therapeutic communication, nurses can collect relevant assessment data, provide education and counseling, and interact during nursing interventions. Sending and receiving messages occur through verbal and nonverbal communication techniques and can happen separately or simultaneously.
Verbal communication depends on language or a prescribed way of using words so that people can share information effectively. The critical aspects of verbal...
5.9K

You might also read

Related Articles

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

Sort by
Same author

Female sex is associated with improved survival after perioperative immunotherapy in resectable non-small cell lung cancer.

Journal of thoracic disease·2026
Same author

Transcatheter Aortic Valve Explant Experience From a High-Volume Structural Heart Center.

Annals of thoracic surgery short reports·2026
Same author

Nighttime Transfer out of Surgical ICU Are Associated With Higher Readmission.

The American surgeon·2026
Same author

Reward expectation drives dogs' choices in a prosocial test.

Animal cognition·2026
Same author

Wolbachia-induced Cytoplasmic Incompatibility drives epigenetic and maternally-influenced post-embryonic defects.

PLoS pathogens·2026
Same author

<i>Wolbachia</i>-induced Cytoplasmic Incompatibility drives epigenetic and maternally-influenced post-embryonic defects.

bioRxiv : the preprint server for biology·2026

Related Experiment Video

Updated: Oct 14, 2025

Protocol for Data Collection and Analysis Applied to Automated Facial Expression Analysis Technology and Temporal Analysis for Sensory Evaluation
07:12

Protocol for Data Collection and Analysis Applied to Automated Facial Expression Analysis Technology and Temporal Analysis for Sensory Evaluation

Published on: August 26, 2016

9.6K

NetFACS: Using network science to understand facial communication systems.

Alexander Mielke1,2, Bridget M Waller3, Claire Pérez1

  • 1Department of Psychology, Centre for Comparative and Evolutionary Psychology, University of Portsmouth, King Henry I Street, Portsmouth, PO1 2DY, UK.

Behavior Research Methods
|November 10, 2021
PubMed
Summary

Researchers developed NetFACS, a new tool for analyzing facial action coding system (FACS) data. This network analysis approach reveals how facial movements (action units) combine, offering insights into animal and human facial communication.

Keywords:
CommunicationFacial action coding systemFacial signalsNetwork analysis

More Related Videos

Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method
08:42

Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method

Published on: September 3, 2021

3.2K
Author Spotlight: Deciphering the Cognitive and Neural Mechanisms of Gesture in Communication
07:18

Author Spotlight: Deciphering the Cognitive and Neural Mechanisms of Gesture in Communication

Published on: January 26, 2024

1.0K

Related Experiment Videos

Last Updated: Oct 14, 2025

Protocol for Data Collection and Analysis Applied to Automated Facial Expression Analysis Technology and Temporal Analysis for Sensory Evaluation
07:12

Protocol for Data Collection and Analysis Applied to Automated Facial Expression Analysis Technology and Temporal Analysis for Sensory Evaluation

Published on: August 26, 2016

9.6K
Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method
08:42

Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method

Published on: September 3, 2021

3.2K
Author Spotlight: Deciphering the Cognitive and Neural Mechanisms of Gesture in Communication
07:18

Author Spotlight: Deciphering the Cognitive and Neural Mechanisms of Gesture in Communication

Published on: January 26, 2024

1.0K

Area of Science:

  • Ethology
  • Bioinformatics
  • Computational Biology

Background:

  • Understanding facial signals is key to evolution and communication.
  • The Facial Action Coding System (FACS) measures facial movements but lacks analytical tools.
  • Network analysis offers a novel approach to analyze FACS data by mapping co-occurring action units (AUs).

Purpose of the Study:

  • Introduce NetFACS, a statistical package for analyzing FACS data using network analysis.
  • Investigate the combinatorial use of AUs in facial communication across species.
  • Provide a dynamic and differentiated approach to studying facial signals.

Main Methods:

  • Developed the NetFACS statistical package.
  • Applied network analysis to FACS datasets, treating AUs as nodes and co-occurrence as connections.
  • Utilized occurrence probabilities and resampling methods for data analysis.

Main Results:

  • Demonstrated that few AUs are context-specific; AUs co-occur rather than acting independently.
  • Showed differences in graph-level properties of stereotypical facial signals.
  • Illustrated that AU clusters can reconstruct facial signals irrespective of underlying conditions.

Conclusions:

  • NetFACS facilitates robust analysis and communication of FACS data.
  • Network analysis reveals the interconnected nature of facial communication.
  • This approach shifts the study of facial signals from stereotyped expressions to a dynamic, differentiated perspective.