title: Line-source modeling and estimation with magnetoencephalography.
abstract: We propose a number of source models that are spatially distributed on a line for magnetoencephalography (MEG) using both a spherical head with radial sensors for more efficient computation and a realistic head model for more accurate results. We develop these models with increasing degrees of freedom, derive forward solutions, maximum-likelihood (ML) estimates, and Cramér-Rao bound (CRB) expressions for the unknown source parameters. A model selection method is applied to select the most appropriate model. We also present numerical examples to compare the performances and computational costs of the different models, to determine the regions where better estimates are possible and when it is possible to distinguish between line and focal sources. We demonstrate the usefulness of the proposed line-source models over the previously available focal source model in certain distributed source cases. Finally, we apply our methods to real MEG data, the N2O response after electric stimulation of the median nerve known to be an extended source.
authors.affiliation: Department of Electrical and Computer Engineering, University of Illinois at Chicago, Chicago, IL 60607, USA. syetik@ece.uic.edu
authors.forename: Imam Samil
authors.initials: IS
authors.lastname: Yetik
authors.forename: Arye
authors.initials: A
authors.lastname: Nehorai
authors.forename: Carlos H
authors.initials: CH
authors.lastname: Muravchik
authors.forename: Jens
authors.initials: J
authors.lastname: Haueisen
mesh_terms: D000465:Algorithms; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods*; D003198:Computer Simulation; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005071:Evoked Potentials / Q000502:physiology; D006801:Humans; D015225:Magnetoencephalography / Q000379:methods*; D008959:Models, Neurological; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity