Fitting a single equivalent current dipole model to MEG data with exhaustive search optimization is a simple, practical and very robust method given the speed of modern computers

2007 ◽  
Vol 1300 ◽  
pp. 121-124 ◽  
Author(s):  
Keith S. Cover ◽  
Jeroen P.A. Verbunt ◽  
Jan C. de Munck ◽  
Bob W. van Dijk
Keyword(s):  
Exhaustive Search ◽  
Dipole Model ◽  
Robust Method ◽  
Equivalent Current Dipole ◽  
Current Dipole ◽  
Equivalent Current ◽  
Search Optimization

scholarly journals Variational Bayesian inversion of the equivalent current dipole model in EEG/MEG

NeuroImage ◽  
2008 ◽  
Vol 39 (2) ◽  
pp. 728-741 ◽  
Author(s):  
Stefan J. Kiebel ◽  
Jean Daunizeau ◽  
Christophe Phillips ◽  
Karl J. Friston
Keyword(s):  
Dipole Model ◽  
Bayesian Inversion ◽  
Equivalent Current Dipole ◽  
Current Dipole ◽  
Equivalent Current ◽  
Variational Bayesian

scholarly journals Clinical Validation of the Champagne Algorithm for Evoked Response Source Localization in Magnetoencephalography

2021 ◽  
Author(s):  
Abhishek S. Bhutada ◽  
Chang Cai ◽  
Danielle Mizuiri ◽  
Anne Findlay ◽  
Jessie Chen ◽  
...  
Keyword(s):  
Evoked Potentials ◽  
Source Localization ◽  
Clinical Population ◽  
Evoked Responses ◽  
Localization Algorithm ◽  
Equivalent Current Dipole ◽  
Current Dipole ◽  
Tumor Patients ◽  
Equivalent Current ◽  
Sensory Evoked

AbstractMagnetoencephalography (MEG) is a robust method for non-invasive functional brain mapping of sensory cortices due to its exceptional spatial and temporal resolution. The clinical standard for MEG source localization of functional landmarks from sensory evoked responses is the equivalent current dipole (ECD) localization algorithm, known to be sensitive to initialization, noise, and manual choice of the number of dipoles. Recently many automated and robust algorithms have been developed, including the Champagne algorithm, an empirical Bayesian algorithm, with powerful abilities for MEG source reconstruction and time course estimation (Wipf et al. 2010; Owen et al. 2012). Here, we evaluate automated Champagne performance in a clinical population of tumor patients where there was minimal failure in localizing sensory evoked responses using the clinical standard, ECD localization algorithm. MEG data of auditory evoked potentials and somatosensory evoked potentials from 21 brain tumor patients were analyzed using Champagne, and these results were compared with equivalent current dipole (ECD) fit. Across both somatosensory and auditory evoked field localization, we found there was a strong agreement between Champagne and ECD localizations in all cases. Given resolution of 8mm voxel size, peak source localizations from Champagne were below 10mm of ECD peak source localization. The Champagne algorithm provides a robust and automated alternative to manual ECD fits for clinical localization of sensory evoked potentials and can contribute to improved clinical MEG data processing workflows.

Elucidation of Equivalent Current Dipole from Magnetocardiography (MCG) Measurements

2011 ◽  
Author(s):  
N. Mariyappa ◽  
M. P. Janawadkar ◽  
T. S. Radhakrishnan ◽  
C. S. Sundar ◽  
S. Sengottuvel ◽  
...  
Keyword(s):  
Equivalent Current Dipole ◽  
Current Dipole ◽  
Equivalent Current

scholarly journals A Software Package for the Modeling of Electrophysiological Activity Data

2022 ◽  
Vol 17 (1) ◽  
pp. 1-10
Author(s):  
A.I. Boyko ◽  
S.D. Rykunov ◽  
M.N. Ustinin
Keyword(s):  
Time Series ◽  
Time Dependence ◽  
Software Package ◽  
Dipole Model ◽  
Input Output ◽  
Equivalent Current Dipole ◽  
Current Dipole ◽  
Output Module ◽  
Calculation Module ◽  
The Brain

A complex of programs has been developed for computer modeling of multichannel time series recorded in various experiments on electromagnetic fields created by the human body. Sets of coordinates and directions of sensors for magnetic encephalographs of several types, electroencephalographs and magnetic cardiographs are used as models of devices. To study the human brain, magnetic resonance tomograms are used as head models; to study the heart, a body model in the form of a half-space with a flat boundary is used. The sources are placed in the model space, for them the direct problem is solved in the physical model corresponding to the device used. For a magnetic encephalograph and an electroencephalograph, an equivalent current dipole model in a spherical conductor is used, for a magnetic cardiograph, an equivalent current dipole model in a flat conductor or a magnetic dipole model is used. For each source, a time dependence is set and a multichannel time series is calculated. Then the time series from all sources are summed and the noise component is added. The program consists of three modules: an input-output module, a calculation module and a visualization module. The input-output module is responsible for loading device models, brain models, and field source parameters. The calculation module is responsible for directly calculating the field and transforming coordinates between the index system and the head system. The visualization module is responsible for the image of the brain model, the position of the field sources, a graphical representation of the amplitude-time dependence of the field sources and the calculated values of the total field. The user interface has been developed. The software package provides: interactive placement of field sources in the head or body space and editing of the amplitude-time dependence; batch loading of a large number of sources; noise modeling; simulation of low-channel planar magnetometers of various orders, specifying the shape of the device, the number of sensors and their parameters. Magnetic and electric fields produced by sources in the brain areas responsible for processing speech stimuli are considered. The resulting multichannel signal can be used to test various data analysis methods and for the experiment planning.

scholarly journals Clinical yield of magnetoencephalography distributed source imaging in epilepsy: A comparison with equivalent current dipole method

2017 ◽  
Vol 39 (1) ◽  
pp. 218-231 ◽  
Author(s):  
Giovanni Pellegrino ◽  
Tanguy Hedrich ◽  
Rasheda Arman Chowdhury ◽  
Jeffery A. Hall ◽  
Francois Dubeau ◽  
...  
Keyword(s):  
Equivalent Current Dipole ◽  
Current Dipole ◽  
Source Imaging ◽  
Distributed Source ◽  
Equivalent Current
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