The role of model and computational experiments in the biomagnetic inverse problem

Publisher Website
Google Scholar
Abstract
This is a review of the role of model and computational experiments in studies of the part of the biomagnetic inverse problem that deals with the determination of electrical sources in the body using magnetic measurements around the body. Results from modelling studies of the forward problem that are important for the inverse problem are also reviewed. An evaluation is made of the adequacy of various models of the body for use in the biomagnetic inverse problem. This evaluation indicates that simple torso models, e.g. a semi-infinite volume or sphere, are probably inadequate. The review of the modelling studies of the inverse problem includes the effects of noise, source modelling errors, body modelling errors and measurement errors on the accuracy of source localisation methods using magnetic measurements. Source modelling errors are caused by differences between an actual complex source in the body and the simple model of it used in most source localisation methods; body modelling errors are caused by differences between the actual body and a simple model of it. The review indicates that typical experimental noise will only cause significant source localisation errors for inverse solutions calculated using fewer than approximately ten measurement points; it also indicates that source modelling errors must be rather large to be detectable when typical experimental noise is present. In addition, the review indicates that many experimental measurement errors will not cause significant localisation errors. The effects of body modelling errors are largely unknown. Suggestions for further biomagnetic inverse problem research are given. These include the development of more realistic models of the body, the experimental verification of such models and source localisation methods, and the development of methods for detecting and localising distributed or multiple discrete sources.

This publication has 18 references indexed in Scilit: