Presentation Title

Electromagnetic modeling of human head for brain source imaging

Location

Reed 330

Start Date

20-4-2017 7:30 PM

Description

Brain source imaging is a sophisticated method for estimating the location of active brain tissues and the temporal course of activity in each active region by means of non-invasive electroencephalography (EEG) and magnetoencephalography (MEG) measurements. The ill-posed nature of the electromagnetic source estimation problem requires of constraints on the brain current sources using anatomical and physiological information. One of the essential elements to achieve the best estimates for the neural currents is an accurate biophysical (forward) model. The accuracy of the model can be accomplished by using individual anatomical information that constitutes the geometry of electrical conductivity in human head and employing a computational method that incorporates the conductivity geometry into the model. Among several ways of realizing the model, finite element method (FEM) is one of the most accurate and flexible approaches. In this presentation, the general procedure of creating the FEM-based forward model is introduced, and the issues of implementing the method into the model is discussed.

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Apr 20th, 7:30 PM

Electromagnetic modeling of human head for brain source imaging

Reed 330

Brain source imaging is a sophisticated method for estimating the location of active brain tissues and the temporal course of activity in each active region by means of non-invasive electroencephalography (EEG) and magnetoencephalography (MEG) measurements. The ill-posed nature of the electromagnetic source estimation problem requires of constraints on the brain current sources using anatomical and physiological information. One of the essential elements to achieve the best estimates for the neural currents is an accurate biophysical (forward) model. The accuracy of the model can be accomplished by using individual anatomical information that constitutes the geometry of electrical conductivity in human head and employing a computational method that incorporates the conductivity geometry into the model. Among several ways of realizing the model, finite element method (FEM) is one of the most accurate and flexible approaches. In this presentation, the general procedure of creating the FEM-based forward model is introduced, and the issues of implementing the method into the model is discussed.