What is a dipole EEG?
In EEG / MEG this is typically represented by a so-called dipole, or dipole source. A dipole is defined by its location (the dipole position) and a vector that represents the strength and orientation of the flow of electric current (the dipole orientation).
What is a Leadfield Matrix?
FT_COMPUTE_LEADFIELD computes a forward solution for a dipole in a a volume conductor model. The forward solution is expressed as the leadfield matrix (Nchan*3), where each column corresponds with the potential or field distributions on all sensors for one of the x,y,z-orientations of the dipole.
What is forward model EEG?
Forward model The process of modeling how data values can be obtained outside of the head with MEG/EEG from electrical current dipoles in the brain is called forward modeling or solving a forward problem.
What is dipole fitting?
Dipole fitting assumes that a small number of point-like equivalent current dipoles (ECDs) can describe the measured topography. It optimises the location, the orientation and the amplitude of the model dipoles in order to minimise the difference between the model and measured topography.
What is the difference between EEG and MEG?
The first obvious difference is that EEG records the electrical activity and MEG records magnetic activity of the brain. MEG primarily detects the magnetic fields induced by intracellular currents, whereas scalp EEG is sensitive to electrical fields generated by extracellular currents.
What are dipoles in the brain?
Electric potentials generated by neurons can be modeled by dipoles (dipole approximation). A dipole is composed of two equal and opposite charges sep- arated by a small distance. The head’s shape distorts the field of the dipoles, particularly those close to the surface, because current cannot flow outside the head.
What are sources of localization?
Localization of active sources of brain is termed as EEG source localization. This process involves the prediction of scalp potentials from the current sources in the brain (forward problem) and the estimation of the location of the sources from scalp potential measurements (termed as inverse problem) [14].
What is the inverse problem EEG?
Simulating the potentials at the electrode positions from current sources inside the brain is known as the EEG forward problem; inference of the position of the current sources from electrode potentials is known as the EEG inverse problem or the neural source imaging problem (Grech et al., 2008, Brannon et al., 2008).
What is the forward problem in EEG?
Background: The aim of electroencephalogram (EEG) source localization is to find the brain areas responsible for EEG waves of interest. It consists of solving forward and inverse problems. The forward problem is solved by starting from a given electrical source and calculating the potentials at the electrodes.
What is the problem with EEG?
Is MEG or EEG better?
The first obvious difference is that EEG records the electrical activity and MEG records magnetic activity of the brain. MEG provides better spatial resolution of source localization (2-3 mm) than EEG (7-10 mm).
Is MEG better than MRI?
Many brain injuries are not visible structurally but show up in brain activation and connectivity which MEG detects and measures. However, MRI scans are a great complement to MEG scan data.
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How is the lead field calculated in BEM?
When the forward solution is computed, the lead field matrix (= channels X source points matrix) is calculated for each grid point taking into account the head model and the channel positions.
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