Biomedical subjects

S Gonzalez Andino

Publications and source records attributed to S Gonzalez Andino.

3 recordsLinked to original sources

PubMed2001

Noninvasive localization of electromagnetic epileptic activity. I. Method descriptions and simulations.

This paper considers the solution of the bioelectromagnetic inverse problem with particular emphasis on focal compact sources that are likely to arise in epileptic data. Two linear inverse methods are proposed and evaluated in simulations. The first method belongs to the class of distributed inverse solutions, capable of dealing with multiple simultaneously active sources. This solution is based on a Local Auto Regressive Average (LAURA) model. Since no assumption is made about the number of activated sources, this approach can be applied to data with multiple sources. The second method, EPIFOCUS, assumes that there is only a single focal source. However, in contrast to the single dipole model, it allows the source to have a spatial extent beyond a single point and avoids the non-linear optimization process required by dipole fitting. The performance of both methods is evaluated with synthetic data in noisy and noise free conditions. The simulation results demonstrate that LAURA and EPIFOCUS increase the number of sources retrieved with zero dipole localization error and produce lower maximum error and lower average error compared to Minimum Norm, Weighted Minimum Norm and Minimum Laplacian (LORETA). The results show that EPIFOCUS is a robust and powerful tool to localize focal sources. Alternatives to localize data generated by multiple sources are discussed. A companion paper (Lantz et al. 2001, this issue) illustrates the application of LAURA and EPIFOCUS to the analysis of interictal data in epileptic patients.

Artifacts↗

PubMed2001

Noninvasive localization of electromagnetic epileptic activity. II. Demonstration of sublobar accuracy in patients with simultaneous surface and depth recordings.

Seven patients with complex partial epileptic seizures undergoing invasive video/EEG-monitoring were investigated with a combination of 10 subdural strip electrode contacts (subtemporal + lateral temporal), and 22 extracranial recording sites. In each patient spikes with different intracranial distributions were identified, and for those with similar distributions the extracranial activity was averaged. A new inverse solution method called EPIFOCUS (Grave et al. 2001, this issue) was used to reconstruct the sources of both single and averaged spikes in a standard 3D-MRI, and a statistical analysis was performed in order to demonstrate location differences between spikes with different intracranial distributions. The results revealed significantly more anterior and ventral source locations for subtemporal compared to lateral temporal spikes. Within the subtemporal group, medial spikes had more mesial and dorsal locations compared to lateral ones. In the lateral temporal group, more anterior and ventral locations were obtained for anterior compared to posterior spikes. The results demonstrate the applicability of EPIFOCUS in the localization of sources in the temporal lobe with sublobar accuracy. This possibility may become important in the future, for instance in identifying cases where amygdalo-hippocampectomy or other limited temporal lobe resections may replace the standard en bloc resections.

Adult↗

PubMed1999

Spatiotemporal EEG analysis and distributed source estimation in presurgical epilepsy evaluation.

In the attempts to localize electric sources in the brain on the basis of multichannel EEG and/or MEG measurements, distributed source estimation procedures have become of increasing interest. Several commercial software packages offer such localization programs and results using these methods are seen more and more frequently in the literature. It is crucial that the users understand the similarities and differences of these methods and that they become aware of the advantages and limitations that are inherent to each approach. This review provides this information from a theoretical as well as from a practical point of view. The theoretical part gives the algorithmic basis of the electromagnetic inverse problem and shows how the different a priori assumptions are formally integrated in these equations. The authors restrict this formalism to the linear inverse solutions i.e., those solutions in which the inversion procedure can be represented as a matrix applied to the data. It will be shown that their properties can be best characterized by their resolution kernels and that methods with optimal resolution matrices can be designed. The authors also discuss the important problem of regularization strategies that are used to minimize the influence of noise. Finally, a new kind of inverse solution, termed ELECTRA (for ELECTRical Analysis), is presented that is based on constraining the source model on the basis of the currents that can actually be measured by the scalp recorded EEG. The practical part of the review illustrates the localization procedures with different clinical data sets. Three aspects become important when working with real data: 1) Clinical data is usually far from ideal (limited number of electrodes, noise, etc.). The behavior of inverse procedures in such unfortunate situations has to be evaluated. 2) The selection of the time points or time periods of interest is crucial, especially in the analysis of spontaneous EEG. 3) Additional information coming from other modalities is usually available and can be incorporated. The authors are illustrating these important points in the case of interictal and ictal epileptiform activity. Spike averaging, frequency domain source localization, and temporal segmentation based on electric field topographies will be discussed. Finally, the technique of EEG-triggered functional magnetic resonance imaging (fMRI) will be illustrated, where EEG is recorded in the magnet and is used to synchronize fMRI acquisition with interictal events. The analysis of both functional data, i.e. the EEG in terms of three-dimensional source localization and the EEG-triggered fMRI, combines the advantages of the two techniques: the temporal resolution of the EEG and the spatial resolution of the fMRI.

Adult↗