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Author

Göran Lantz

Other affiliations: Geneva College
Bio: Göran Lantz is an academic researcher from University of Geneva. The author has contributed to research in topics: Electroencephalography & Epilepsy. The author has an hindex of 15, co-authored 21 publications receiving 3450 citations. Previous affiliations of Göran Lantz include Geneva College.

Papers
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Journal ArticleDOI
TL;DR: It is shown that modern EEG source imaging simultaneously details the temporal and spatial dimensions of brain activity, making it an important and affordable tool to study the properties of cerebral, neural networks in cognitive and clinical neurosciences.

1,600 citations

Journal ArticleDOI
TL;DR: The results illustrate the necessity of multichannel EEG recordings for high source location accuracy in epileptic patients and confirm the relation between the number of electrodes and localization accuracy.

375 citations

Journal ArticleDOI
TL;DR: 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 and proposes and evaluates two linear inverse methods, LAURA and EPIFOCUS.
Abstract: 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.

364 citations

Journal ArticleDOI
TL;DR: 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, demonstrating the applicability of EPIFOCUS in the localization of sources in the temporal lobe with sublobar accuracy.
Abstract: 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.

251 citations

Journal ArticleDOI
TL;DR: The proposed spherical model, that is called SMAC (Spherical Model with Anatomical Constrains) is tested with simulations, as well as with the following real data: estimation of the sources of visual evoked potentials to unilateral stimulation from data averaged over subjects, and localization of interictal discharges of two epileptic patients.
Abstract: Two classes of functional neuroimaging methods exist: hemodynamic techniques such as PET and fMRI, and electromagnetic techniques such as EEG/ERP and MEG. In order to fusion these images with anatomical information, co-registration with volumetric MRI is needed. While such co-registration techniques are well established for hemodynamic images, additional steps are needed for electromagnetic recordings, because the activity is only recorded on the scalp surface and inverse solutions based on specific head models have to be used to estimate the 3-dimensional current distribution. To date most of the experimental and clinical studies use multi-shell concentric sphere models of the head, solve the inverse problem on this simplistic model, and then co-register the solution with the MRI using homogeneous transform operations. Contrary to this standard method, we here propose to map the MRI to the spherical system by defining transformation operations that transform the MRI to a best-fitting sphere. Once done so, the solution points are defined in the cerebral tissue of this deformed MRI and the lead field for the distributed linear inverse solutions is calculated for this solution space. The method, that we call SMAC (Spherical Model with Anatomical Constrains) is tested with simulations, as well as with the following real data: 1) estimation of the sources of visual evoked potentials to unilateral stimulation from data averaged over subjects, and 2) localization of interictal discharges of two epileptic patients, one with a temporal, the other with an occipital focus, both confirmed by seizure freedom after resection of the epileptogenic region.

189 citations


Cited by
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Journal Article
TL;DR: The technical details of the method are presented, allowing researchers to test, check, reproduce and validate the new method, and a solution reported here yields images of standardized current density with zero localization error.
Abstract: Scalp electric potentials (electroencephalograms) and extracranial magnetic fields (magnetoencephalograms) are due to the primary (impressed) current density distribution that arises from neuronal postsynaptic processes. A solution to the inverse problem--the computation of images of electric neuronal activity based on extracranial measurements--would provide important information on the time-course and localization of brain function. In general, there is no unique solution to this problem. In particular, an instantaneous, distributed, discrete, linear solution capable of exact localization of point sources is of great interest, since the principles of linearity and superposition would guarantee its trustworthiness as a functional imaging method, given that brain activity occurs in the form of a finite number of distributed hot spots. Despite all previous efforts, linear solutions, at best, produced images with systematic nonzero localization errors. A solution reported here yields images of standardized current density with zero localization error. The purpose of this paper is to present the technical details of the method, allowing researchers to test, check, reproduce and validate the new method.

3,085 citations

Journal ArticleDOI
TL;DR: It is shown that modern EEG source imaging simultaneously details the temporal and spatial dimensions of brain activity, making it an important and affordable tool to study the properties of cerebral, neural networks in cognitive and clinical neurosciences.

1,600 citations

Journal Article
TL;DR: For instance, this paper found that brain activation in males is lateralized to the left inferior frontal gyrus regions; in females the pattern of activation is very different, engaging more diffuse neural systems that involve both the left and right inferior frontal cortex.
Abstract: A MUCH debated question is whether sex differences exist in the functional organization of the brain for language1–4. A long-held hypothesis posits that language functions are more likely to be highly lateralized in males and to be represented in both cerebral hemispheres in females5,6, but attempts to demonstrate this have been inconclusive7–17. Here we use echo-planar functional magnetic resonance imaging18–21 to study 38 right-handed subjects (19 males and 19 females) during orthographic (letter recognition), phonological (rhyme) and semantic (semantic category) tasks. During phonological tasks, brain activation in males is lateralized to the left inferior frontal gyrus regions; in females the pattern of activation is very different, engaging more diffuse neural systems that involve both the left and right inferior frontal gyrus. Our data provide clear evidence for a sex difference in the functional organization of the brain for language and indicate that these variations exist at the level of phonological processing.

1,247 citations

Journal ArticleDOI
TL;DR: The Monte-Carlo analysis performed, comparing WMN, LORETA, sLorETA and SLF, for different noise levels and different simulated source depths has shown that for single source localization, regularized sLORETA gives the best solution in terms of both localization error and ghost sources.
Abstract: In this primer, we give a review of the inverse problem for EEG source localization. This is intended for the researchers new in the field to get insight in the state-of-the-art techniques used to find approximate solutions of the brain sources giving rise to a scalp potential recording. Furthermore, a review of the performance results of the different techniques is provided to compare these different inverse solutions. The authors also include the results of a Monte-Carlo analysis which they performed to compare four non parametric algorithms and hence contribute to what is presently recorded in the literature. An extensive list of references to the work of other researchers is also provided. This paper starts off with a mathematical description of the inverse problem and proceeds to discuss the two main categories of methods which were developed to solve the EEG inverse problem, mainly the non parametric and parametric methods. The main difference between the two is to whether a fixed number of dipoles is assumed a priori or not. Various techniques falling within these categories are described including minimum norm estimates and their generalizations, LORETA, sLORETA, VARETA, S-MAP, ST-MAP, Backus-Gilbert, LAURA, Shrinking LORETA FOCUSS (SLF), SSLOFO and ALF for non parametric methods and beamforming techniques, BESA, subspace techniques such as MUSIC and methods derived from it, FINES, simulated annealing and computational intelligence algorithms for parametric methods. From a review of the performance of these techniques as documented in the literature, one could conclude that in most cases the LORETA solution gives satisfactory results. In situations involving clusters of dipoles, higher resolution algorithms such as MUSIC or FINES are however preferred. Imposing reliable biophysical and psychological constraints, as done by LAURA has given superior results. The Monte-Carlo analysis performed, comparing WMN, LORETA, sLORETA and SLF, for different noise levels and different simulated source depths has shown that for single source localization, regularized sLORETA gives the best solution in terms of both localization error and ghost sources. Furthermore the computationally intensive solution given by SLF was not found to give any additional benefits under such simulated conditions.

1,013 citations

Journal ArticleDOI
TL;DR: Positive emotions evoked N170 significantly earlier than negative emotions and the amplitude of N170 evoked by fearful faces was larger than neutral or surprised faces, which support a model of automatic, rapid processing of emotional expressions.

929 citations