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

Variation: Normal Distribution, Range, and Standard Deviation02:32

Variation: Normal Distribution, Range, and Standard Deviation

27.0K
In the field of psychology, there are several ways to organize measurements of a trait, feature, or characteristic (i.e., variables). Qualitative data, such as ethnicity, can be tabulated into a frequency count to provide information about the proportion, as well as the variety of groups in a sample or population. On the other hand, researchers can perform a wider set of calculations on quantitative data. The mean, mode, and median, for instance, are central tendency measures to identify a...
27.0K
The Electromagnetic Spectrum02:37

The Electromagnetic Spectrum

64.9K
The electromagnetic spectrum consists of all the types of electromagnetic radiation arranged according to their frequency and wavelength. Each of the various colors of visible light has specific frequencies and wavelengths associated with them, and you can see that visible light makes up only a small portion of the electromagnetic spectrum. Because the technologies developed to work in various parts of the electromagnetic spectrum are different, for reasons of convenience and historical...
64.9K
Synthesis and Decomposition Reactions02:17

Synthesis and Decomposition Reactions

38.1K
Synthesis and decomposition are two types of redox reactions. Synthesis means to make something, whereas decomposition means to break something. The reactions are accompanied by chemical and energy changes. 
38.1K
What is Variation?01:14

What is Variation?

17.6K
Apart from the measures of central tendency, distribution, outliers, and the changing characteristics of data with time, an important characteristic of any data set is its variation or spread. In some data sets, the data values are concentrated closely near the mean; in others, the data values are more widely spread out from the mean.
The range, standard deviation, standard error, and variance are the different measures of variation.
Range: The range is the difference between its maximum and...
17.6K
Long-term Depression01:05

Long-term Depression

33.2K
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.
33.2K
Freezing Point Depression and Boiling Point Elevation03:12

Freezing Point Depression and Boiling Point Elevation

39.7K
Boiling Point Elevation
The boiling point of a liquid is the temperature at which its vapor pressure is equal to ambient atmospheric pressure. Since the vapor pressure of a solution is lowered due to the presence of nonvolatile solutes, it stands to reason that the solution’s boiling point will subsequently be increased. Vapor pressure increases with temperature, and so a solution will require a higher temperature than will pure solvent to achieve any given vapor pressure, including one...
39.7K

You might also read

Related Articles

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

Sort by
Same author

Generalization of AI-Based Gestational Age Assessment Using Blind Sweep Ultrasonography.

JAMA network open·2026
Same author

A wearable biosensing platform for continuous monitoring of inflammatory and metabolic biomarkers for real-time health tracking and personalized care.

Bioengineering & translational medicine·2026
Same author

Shelf life and time-resolved thermal, chemical, and thermodynamic characterization of four hydrophobic deep eutectic solvents.

RSC advances·2026
Same author

Enhancing Postharvest quality and shelf life of 'Zardalu' mango using melatonin treatment during ambient storage.

Plant science : an international journal of experimental plant biology·2026
Same author

Role of Ayurvedic Principles in Addressing Malnutrition and Non-Communicable Diseases in Low-Resource Settings.

Cureus·2026
Same author

From forest floor to doctor's office: the immunological journey of <i>Borrelia burgdorferi</i> through vertebrate hosts.

Frontiers in immunology·2026

Related Experiment Video

Updated: Jan 24, 2026

Micron-scale Resolution Optical Tomography of Entire Mouse Brains with Confocal Light Sheet Microscopy
09:49

Micron-scale Resolution Optical Tomography of Entire Mouse Brains with Confocal Light Sheet Microscopy

Published on: October 8, 2013

17.1K

Electroencephalography-Based Source Localization for Depression Using Standardized Low Resolution Brain

Chamandeep Kaur1, Preeti Singh2, Sukhtej Sahni3

  • 1Department of Electronics and Communication Engineering, University Institute of Engineering and Technology, Panjab University Chandigarh, Chandigarh, India.

European Neurology
|May 22, 2019
PubMed
Summary
This summary is machine-generated.

This study introduces a new EEG source localization method combining variational mode decomposition (VMD) and standardized low resolution brain electromagnetic tomography (sLORETA) for depression diagnosis. The approach improves accuracy by reducing noise in EEG signals, aiding in earlier detection.

Keywords:
DenoisingDepressionElectroencephalographyInverse modelingStandardized low-resolution brain electromagnetic tomography

More Related Videos

Brain Source Imaging in Preclinical Rat Models of Focal Epilepsy using High-Resolution EEG Recordings
08:20

Brain Source Imaging in Preclinical Rat Models of Focal Epilepsy using High-Resolution EEG Recordings

Published on: June 6, 2015

15.8K
Electromagnetic Navigation Transthoracic Nodule Localization for Minimally Invasive Thoracic Surgery
07:30

Electromagnetic Navigation Transthoracic Nodule Localization for Minimally Invasive Thoracic Surgery

Published on: May 4, 2022

3.7K

Related Experiment Videos

Last Updated: Jan 24, 2026

Micron-scale Resolution Optical Tomography of Entire Mouse Brains with Confocal Light Sheet Microscopy
09:49

Micron-scale Resolution Optical Tomography of Entire Mouse Brains with Confocal Light Sheet Microscopy

Published on: October 8, 2013

17.1K
Brain Source Imaging in Preclinical Rat Models of Focal Epilepsy using High-Resolution EEG Recordings
08:20

Brain Source Imaging in Preclinical Rat Models of Focal Epilepsy using High-Resolution EEG Recordings

Published on: June 6, 2015

15.8K
Electromagnetic Navigation Transthoracic Nodule Localization for Minimally Invasive Thoracic Surgery
07:30

Electromagnetic Navigation Transthoracic Nodule Localization for Minimally Invasive Thoracic Surgery

Published on: May 4, 2022

3.7K

Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Signal Processing

Background:

  • Electroencephalography (EEG) is a valuable tool for diagnosing neurological disorders.
  • EEG source localization is crucial for real-time brain monitoring but faces accuracy challenges due to the inverse problem.
  • Existing methods struggle with noise, impacting diagnostic precision.

Purpose of the Study:

  • To develop and evaluate a novel EEG source localization method for diagnosing depression.
  • To enhance the accuracy of EEG signal processing in clinical applications.
  • To compare the proposed method's effectiveness on real EEG data from depression patients.

Main Methods:

  • Variational Mode Decomposition (VMD) was used to decompose real EEG recordings from depression patients into distinct mode functions.
  • Standardized Low Resolution Brain Electromagnetic Tomography (sLORETA) was applied for inverse modeling and source localization of the decomposed EEG signals.
  • Simulations on real EEG databases for depression were conducted to validate the proposed techniques.

Main Results:

  • The proposed VMD-sLORETA method demonstrated improved accuracy and robustness in EEG source localization for depression.
  • Performance was assessed using localization error (LE), mean square error, and signal-to-noise ratio, showing effective noise suppression.
  • The study highlighted the methodology's potential for precise spatial resolution of cortical potential distribution.

Conclusions:

  • The developed algorithm effectively mitigates noise interference in EEG inverse problems, crucial for depression signal analysis.
  • This approach offers a promising pre-processing step for automated depression detection systems, potentially reducing diagnostic delays.
  • The findings suggest a significant advancement in objective diagnostic tools for mental health disorders using EEG.