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

You might also read

Related Articles

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

Sort by
Same author

Decoding visual object recognition from EEG signals.

PloS one·2026
Same author

Nanoelectronic Detection of Opioids: Machine Learning-Powered Screening With Carbon Nanotube Field-Effect Transistor Sensor Array.

Small (Weinheim an der Bergstrasse, Germany)·2026
Same author

Racial and Ethnic Disparities in Dysphagia Care Access, Utilization, and Quality in the United States: A Scoping Review.

Dysphagia·2026
Same author

Novel machine learning fusion architectures integrating electrocardiogram representations: applications to acute coronary event detection.

European heart journal. Digital health·2026
Same author

Enhancing generalizability in classification of peripheral neural recordings with graph neural network.

PloS one·2026
Same author

Urinary Cytokines in Predicting Intradetrusor Onabotulinumtoxin-A Response.

Neurourology and urodynamics·2026

Related Experiment Video

Updated: Mar 10, 2026

fMRI Mapping of Brain Activity Associated with the Vocal Production of Consonant and Dissonant Intervals
11:15

fMRI Mapping of Brain Activity Associated with the Vocal Production of Consonant and Dissonant Intervals

Published on: May 23, 2017

7.7K

Differences in brain networks during consecutive swallows detected using an optimized vertex-frequency algorithm.

Iva Jestrović1, James L Coyle2, Ervin Sejdić1

  • 1Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA 15261, USA.

Neuroscience
|December 20, 2016
PubMed
Summary
This summary is machine-generated.

Consecutive swallowing impacts brain activity, with thicker liquids causing greater neural network changes. This study reveals how brain networks adapt during repetitive swallowing in healthy individuals.

Keywords:
dysphagiaelectroencephalographygraph signal processingswallowingvertex–frequency analysis

More Related Videos

Analyzing Neural Activity and Connectivity Using Intracranial EEG Data with SPM Software
06:50

Analyzing Neural Activity and Connectivity Using Intracranial EEG Data with SPM Software

Published on: October 30, 2018

10.0K
Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms
08:36

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms

Published on: March 21, 2019

7.7K

Related Experiment Videos

Last Updated: Mar 10, 2026

fMRI Mapping of Brain Activity Associated with the Vocal Production of Consonant and Dissonant Intervals
11:15

fMRI Mapping of Brain Activity Associated with the Vocal Production of Consonant and Dissonant Intervals

Published on: May 23, 2017

7.7K
Analyzing Neural Activity and Connectivity Using Intracranial EEG Data with SPM Software
06:50

Analyzing Neural Activity and Connectivity Using Intracranial EEG Data with SPM Software

Published on: October 30, 2018

10.0K
Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms
08:36

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms

Published on: March 21, 2019

7.7K

Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Signal Processing

Background:

  • Repetitive swallowing can lead to aspiration risk in dysphagia patients due to the fatigue effect.
  • The impact of consecutive swallows on brain activity and neural networks remains largely unexplored.
  • Understanding these neural dynamics is crucial for assessing swallowing function and developing interventions.

Purpose of the Study:

  • To investigate the differences in brain network activity during consecutive swallows.
  • To apply a novel signal processing on graph approach to analyze electroencephalography (EEG) data during swallowing.
  • To explore how liquid viscosity affects brain network responses during repetitive swallowing.

Main Methods:

  • Collected EEG data from 55 healthy participants performing dry and wet swallows (varying viscosities).
  • Employed a signal processing on graph approach, including time-frequency-based synchrony measures to construct brain networks.
  • Utilized optimized windowed graph Fourier transform and graph S-transform algorithms for analyzing vertex frequency information.

Main Results:

  • Demonstrated significant differences in brain activity between consecutive swallows using the developed EEG analysis methods.
  • Identified distinct patterns in brain network activity related to swallowing effort and fatigue.
  • Observed greater differences in brain activity between consecutive swallows for thicker liquids (nectar-thick, honey-thick) compared to water and dry swallows.

Conclusions:

  • Consecutive swallows induce measurable changes in brain network activity.
  • The viscosity of ingested liquids influences the neural response during repetitive swallowing.
  • This research provides a novel method for analyzing brain dynamics in swallowing and has implications for understanding dysphagia and fatigue effects.