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

Brain Imaging01:14

Brain Imaging

209
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...
209
Action Potential01:31

Action Potential

7.8K
Neurons communicate by firing action potentials—the electrochemical signal that is propagated along the axon. The signal results in the release of neurotransmitters at axon terminals, thereby transmitting information to the nervous system. An action potential is a specific "all-or-none" change in membrane potential that results in a rapid spike in voltage.
Membrane potential in neurons
Neurons typically have a resting membrane potential of about -70 millivolts (mV). When they...
7.8K

You might also read

Related Articles

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

Sort by
Same author

North-South asymmetry of Parkinson's disease mortality in Brazil between 2009 and 2023: a spatial analysis.

Scientific reports·2026
Same author

Brain state dependent repetitive transcranial magnetic stimulation improves motor learning outcomes.

Journal of neural engineering·2026
Same author

Decoding semantic categories: insights from an fMRI ALE meta analysis.

Journal of neural engineering·2025
Same author

Speech imagery brain-computer interfaces: a systematic literature review.

Journal of neural engineering·2025
Same author

Simultaneous EEG and fNIRS recordings for semantic decoding of imagined animals and tools.

Scientific data·2025
Same author

Alpha-Oscillatory Current Application Impacts Prospective Remembering Through Strategic Monitoring.

Psychophysiology·2025

Related Experiment Video

Updated: Jun 5, 2025

A Multimodal Imaging- and Stimulation-based Method of Evaluating Connectivity-related Brain Excitability in Patients with Epilepsy
08:23

A Multimodal Imaging- and Stimulation-based Method of Evaluating Connectivity-related Brain Excitability in Patients with Epilepsy

Published on: November 13, 2016

11.1K

TMS-evoked potential propagation reflects effective brain connectivity.

Ian Daly1, Nitin Williams2,3, Slawomir J Nasuto4

  • 1Brain-Computer Interfacing and Neural Engineering Laboratory, School of Computer Science and Electronic Engineering, University of Essex, Colchester, United Kingdom.

Journal of Neural Engineering
|December 13, 2024
PubMed
Summary
This summary is machine-generated.

Visual feedback impacts brain connectivity. Transcranial magnetic stimulation (TMS) evoked potentials (TEPs) reveal differences in how brain regions communicate, offering a new way to map effective connectivity during motor control.

Keywords:
EEGMVARTEPTMSbrain connectivity

More Related Videos

Brain State-dependent Brain Stimulation with Real-time Electroencephalography-Triggered Transcranial Magnetic Stimulation
00:08

Brain State-dependent Brain Stimulation with Real-time Electroencephalography-Triggered Transcranial Magnetic Stimulation

Published on: August 20, 2019

14.2K
Extracting Visual Evoked Potentials from EEG Data Recorded During fMRI-guided Transcranial Magnetic Stimulation
09:36

Extracting Visual Evoked Potentials from EEG Data Recorded During fMRI-guided Transcranial Magnetic Stimulation

Published on: May 12, 2014

13.8K

Related Experiment Videos

Last Updated: Jun 5, 2025

A Multimodal Imaging- and Stimulation-based Method of Evaluating Connectivity-related Brain Excitability in Patients with Epilepsy
08:23

A Multimodal Imaging- and Stimulation-based Method of Evaluating Connectivity-related Brain Excitability in Patients with Epilepsy

Published on: November 13, 2016

11.1K
Brain State-dependent Brain Stimulation with Real-time Electroencephalography-Triggered Transcranial Magnetic Stimulation
00:08

Brain State-dependent Brain Stimulation with Real-time Electroencephalography-Triggered Transcranial Magnetic Stimulation

Published on: August 20, 2019

14.2K
Extracting Visual Evoked Potentials from EEG Data Recorded During fMRI-guided Transcranial Magnetic Stimulation
09:36

Extracting Visual Evoked Potentials from EEG Data Recorded During fMRI-guided Transcranial Magnetic Stimulation

Published on: May 12, 2014

13.8K

Area of Science:

  • Neuroscience
  • Cognitive Science
  • Biomedical Engineering

Background:

  • Cognition relies on brain region communication, necessitating effective connectivity measures.
  • Transcranial magnetic stimulation (TMS) evoked potentials (TEPs) are a promising metric for effective connectivity but require further validation.
  • Existing statistical methods for effective connectivity, like multivariate auto-regressive modeling, provide a benchmark for comparison.

Purpose of the Study:

  • To investigate TEPs as a measure of effective connectivity.
  • To compare TEP-based effective connectivity measures with established statistical methods.
  • To examine how visual feedback during motor control influences effective connectivity.

Main Methods:

  • Utilized a pre-existing experimental dataset comparing TEPs during a motor control task with and without visual feedback.
  • Analyzed TEPs to assess differences in brain region communication.
  • Compared TEP-derived effective connectivity metrics against multivariate auto-regressive modeling results.

Main Results:

  • Significantly more negative TEPs (40-100 ms post-TMS) were observed over frontal and central channels without visual feedback.
  • Significantly more positive later TEPs (280-400 ms) appeared on contralateral motor and parietal channels without feedback.
  • Early TEP variations (N40) showed a reliable relationship with directed coherence, a statistical measure of connectivity.

Conclusions:

  • Components of TEPs function as effective measures of brain connectivity.
  • Effective connectivity is a dynamic process influenced by factors like visual feedback.
  • TEPs are valuable for mapping region-to-region changes in effective connectivity, particularly in motor control contexts.