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

Area Computation by the Alternative Coordinate Method01:24

Area Computation by the Alternative Coordinate Method

700
The alternative coordinate method, also known as the Shoelace Formula, is a technique for determining the area of a traverse using Cartesian coordinates. This method relies on the sequential arrangement of x and y coordinates for each point of the shape, ensuring accuracy and ease of application.In this approach, each corner's x and y coordinates are listed as fractions, with the x-coordinate as the numerator and the y-coordinate as the denominator. These coordinates are arranged sequentially...
700
Extraction: Partition and Distribution Coefficients01:14

Extraction: Partition and Distribution Coefficients

5.2K
The distribution law or Nernst's distribution law is the law that governs the distribution of a solute between two immiscible solvents. This law, also known as the partition law, states that if a solute is added to the mixture of two immiscible solvents at a constant temperature, the solute is distributed between the two solvents in such a way that the ratio of solute concentrations in the solvents remains constant at equilibrium.
For extracting a solute from an aqueous phase into an...
5.2K
Vector Algebra: Method of Components01:08

Vector Algebra: Method of Components

20.2K
It is cumbersome to find the magnitudes of vectors using the parallelogram rule or using the graphical method to perform mathematical operations like addition, subtraction, and multiplication. There are two ways to circumvent this algebraic complexity. One way is to draw the vectors to scale, as in navigation, and read approximate vector lengths and angles (directions) from the graphs. The other way is to use the method of components.
In many applications, the magnitudes and directions of...
20.2K
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

449
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence of...
449
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

1.3K
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
1.3K
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

409
Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
409

You might also read

Related Articles

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

Sort by
Same author

Chronic metal contamination shapes the size structure of Gammarus fossarum populations in French headwater rivers.

Ecotoxicology (London, England)·2024
Same author

Quantitative brainstem and spinal MRI in amyotrophic lateral sclerosis: implications for predicting noninvasive ventilation needs.

Journal of neurology·2023
Same author

Avoidance behaviour of aquatic macroinvertebrates for real-time detection of micropollutant surge in wastewater effluents.

Water research·2023
Same author

Comparison of spinal magnetic resonance imaging and classical clinical factors in predicting motor capacity in amyotrophic lateral sclerosis.

Journal of neurology·2023
Same author

EEG neurofeedback research: A fertile ground for psychiatry?

L'Encephale·2019
Same author

Dramatic Increase in Incidence of Ulcerative Colitis and Crohn's Disease (1988-2011): A Population-Based Study of French Adolescents.

The American journal of gastroenterology·2017

Related Experiment Video

Updated: Mar 3, 2026

Detecting Pre-Stimulus Source-Level Effects on Object Perception with Magnetoencephalography
09:25

Detecting Pre-Stimulus Source-Level Effects on Object Perception with Magnetoencephalography

Published on: July 26, 2019

7.4K

Multivariate source prelocalization (MSP): use of functionally informed basis functions for better conditioning the

J Mattout1, M Pélégrini-Issac, L Garnero

  • 1Wellcome Department of Imaging Neuroscience, London, UK. jmattout@fil.ion.ucl.ac.uk

Neuroimage
|May 24, 2005
PubMed
Summary

This study introduces a novel preprocessing tool for magnetoencephalography/electroencephalography (MEG/EEG) data. It improves brain source localization by using intrinsic data properties, enhancing the accuracy of neuroimaging analysis.

More Related Videos

Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging
11:28

Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging

Published on: June 30, 2018

12.4K
Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
08:45

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Published on: October 24, 2012

15.3K

Related Experiment Videos

Last Updated: Mar 3, 2026

Detecting Pre-Stimulus Source-Level Effects on Object Perception with Magnetoencephalography
09:25

Detecting Pre-Stimulus Source-Level Effects on Object Perception with Magnetoencephalography

Published on: July 26, 2019

7.4K
Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging
11:28

Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging

Published on: June 30, 2018

12.4K
Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
08:45

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Published on: October 24, 2012

15.3K

Area of Science:

  • Neuroscience
  • Biophysics
  • Computational Biology

Background:

  • Magnetoencephalography (MEG) and electroencephalography (EEG) are crucial for understanding brain activity.
  • Solving the inverse problem for MEG/EEG data is challenging due to non-unique solutions.
  • Current methods often rely on external anatomical or functional priors.

Purpose of the Study:

  • To develop a preprocessing tool for improved MEG/EEG source reconstruction.
  • To enhance the localization accuracy of brain activity.
  • To introduce a method relying solely on intrinsic data and forward models.

Main Methods:

  • Defined subject-specific, functionally Informed Basis Functions (fIBF) based on realistic cortical models.
  • Proposed a Multivariate Source Prelocalization (MSP) method using fIBF to estimate activation coefficients.
  • Utilized these coefficients as intrinsic functional priors to constrain source reconstruction.

Main Results:

  • Demonstrated the effectiveness of the MSP approach on simulated and real MEG data.
  • Showcased how MSP improves the conditioning of source reconstruction.
  • Quantitatively evaluated the performance enhancement in a standard regularization framework.

Conclusions:

  • The MSP approach offers a robust method for pre-processing MEG/EEG data.
  • It effectively addresses the ill-posed nature of the inverse problem by providing intrinsic functional priors.
  • This technique enhances the reliability and accuracy of brain activity localization.