Improved dipole localization using local mesh refinement of realistic head geometries: an EEG simulation study

The Sensitivity of Ear-EEG: Evaluating the Source-Sensor Relationship Using Forward Modeling

Ear-EEG allows to record brain activity in every-day life, for example to study natural behaviour or unhindered social interactions. Compared to conventional scalp-EEG, ear-EEG uses fewer electrodes and covers only a small part of the head. Consequently, ear-EEG will be less sensitive to some cortical sources. Here, we perform realistic electromagnetic simulations to compare cEEGrid ear-EEG with 128-channel cap-EEG. We compute the sensitivity of ear-EEG for different cortical sources, and quantify the expected signal loss of ear-EEG relative to cap-EEG. Our results show that ear-EEG is most sensitive to sources in the temporal cortex. Furthermore, we show how ear-EEG benefits from a multi-channel configuration (i.e. cEEGrid). The pipelines presented here can be adapted to any arrangement of electrodes and can therefore provide an estimate of sensitivity to cortical regions, thereby increasing the chance of successful experiments using ear-EEG.

Variability of magnetoencephalographic sensor sensitivity measures as a function of age, brain volume and cortical area

OBJECTIVE

To assess the feasibility and appropriateness of magnetoencephalography (MEG) for both adult and pediatric studies, as well as for the developmental comparison of these factors across a wide range of ages.

METHODS

For 45 subjects with ages from 1 to 24years (infants, toddlers, school-age children and young adults), lead fields (LFs) of MEG sensors are computed using anatomically realistic boundary element models (BEMs) and individually-reconstructed cortical surfaces. Novel metrics are introduced to quantify MEG sensor focality.

RESULTS

The variability of MEG focality is graphed as a function of brain volume and cortical area. Statistically significant differences in total cerebral volume, cortical area, MEG global sensitivity and LF focality are found between age groups.

CONCLUSIONS

Because MEG focality and sensitivity differ substantially across the age groups studied, the cortical LF maps explored here can provide important insights for the examination and interpretation of MEG signals from early childhood to young adulthood.

SIGNIFICANCE

This is the first study to (1) investigate the relationship between MEG cortical LFs and brain volume as well as cortical area across development, and (2) compare LFs between subjects with different head sizes using detailed cortical reconstructions.

Sensitivity of MEG and EEG to source orientation

An important difference between magnetoencephalography (MEG) and electroencephalography (EEG) is that MEG is insensitive to radially oriented sources. We quantified computationally the dependency of MEG and EEG on the source orientation using a forward model with realistic tissue boundaries. Similar to the simpler case of a spherical head model, in which MEG cannot see radial sources at all, for most cortical locations there was a source orientation to which MEG was insensitive. The median value for the ratio of the signal magnitude for the source orientation of the lowest and the highest sensitivity was 0.06 for MEG and 0.63 for EEG. The difference in the sensitivity to the source orientation is expected to contribute to systematic differences in the signal-to-noise ratio between MEG and EEG.

Cancellation of EEG and MEG signals generated by extended and distributed sources

Extracranial patterns of scalp potentials and magnetic fields, as measured with electro- and magnetoencephalography (EEG, MEG), are spatially widespread even when the underlying source in the brain is focal. Therefore, loss in signal magnitude due to cancellation is expected when multiple brain regions are simultaneously active. We characterized these cancellation effects in EEG and MEG using a forward model with sources constrained on an anatomically accurate reconstruction of the cortical surface. Prominent cancellation was found for both EEG and MEG in the case of multiple randomly distributed source dipoles, even when the number of simultaneous dipoles was small. Substantial cancellation occurred also for locally extended patches of simulated activity, when the patches extended to opposite walls of sulci and gyri. For large patches, a difference between EEG and MEG cancellation was seen, presumably due to selective cancellation of tangentially vs. radially oriented sources. Cancellation effects can be of importance when electrophysiological data are related to hemodynamic measures. Furthermore, the selective cancellation may be used to explain some observed differences between EEG and MEG in terms of focal vs. widespread cortical activity.

EEG source imaging

OBJECTIVE

Electroencephalography (EEG) is an important tool for studying the temporal dynamics of the human brain's large-scale neuronal circuits. However, most EEG applications fail to capitalize on all of the data's available information, particularly that concerning the location of active sources in the brain. Localizing the sources of a given scalp measurement is only achieved by solving the so-called inverse problem. By introducing reasonable a priori constraints, the inverse problem can be solved and the most probable sources in the brain at every moment in time can be accurately localized.

METHODS AND RESULTS

Here, we review the different EEG source localization procedures applied during the last two decades. Additionally, we detail the importance of those procedures preceding and following source estimation that are intimately linked to a successful, reliable result. We discuss (1) the number and positioning of electrodes, (2) the varieties of inverse solution models and algorithms, (3) the integration of EEG source estimations with MRI data, (4) the integration of time and frequency in source imaging, and (5) the statistical analysis of inverse solution results.

CONCLUSIONS AND SIGNIFICANCE

We show 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.

Dipole localization accuracy using grand-average EEG data sets

OBJECTIVE

Dipole localization of grand-average event related potentials only give a tentative description of the estimated underlying neural sources. This study evaluates the differences in dipole solutions between individual and group-average data sets using a standard realistic head model.

METHODS

Auditory evoked potentials were recorded from 14 right-handed healthy subjects using a 64 electrode montage. Inverse dipole solutions were obtained for each individual data set, as well as for all individual responses averaged together (grand-average). Differences in dipole solutions between individual and grand-average responses are reported. Simulations using a two dipole model with 15 different electrode sets are then used to investigate the effects of electrode misplacement and random noise on dipole localization. These effects are compared to those due to grand-averaging.

RESULTS

The average differences in dipole locations between the individual and grand-averaged data sets were approximately 1.1 cm (SD=0.7 cm). This difference is larger than typical localization errors due to electrode misplacement and typical noise.

CONCLUSIONS

Using a standard realistic head model, it is concluded that dipole solutions based on group-averaged EEG datasets are significantly different than those obtained using subject-specific data.

Effects of skull thickness, anisotropy, and inhomogeneity on forward EEG/ERP computations using a spherical three-dimensional resistor mesh model

Bone thickness, anisotropy, and inhomogeneity have been reported to induce important variations in electroencephalogram (EEG) scalp potentials. To study this effect, we used an original three-dimensional (3-D) resistor mesh model described in spherical coordinates, consisting of 67,464 elements and 22,105 nodes arranged in 36 different concentric layers. After validation of the model by comparison with the analytic solution, potential variations induced by geometric and electrical skull modifications were investigated at the surface in the dipole plane and along the dipole axis, for several eccentricities and bone thicknesses. The resistor mesh permits one to obtain various configurations, as local modifications are introduced very easily. This has allowed several head models to be designed to study the effects of skull properties (thickness, anisotropy, and heterogeneity) on scalp surface potentials. Results show a decrease of potentials in bone, depending on bone thickness, and a very small decrease through the scalp layer. Nevertheless, similar scalp potentials can be obtained using either a thick scalp layer and a thin skull layer, and vice versa. It is thus important to take into account skull and scalp thicknesses, because the drop of potential in bone depends on both. The use of three different layers for skull instead of one leads to small differences in potential values and patterns. In contrast, the introduction of a hole in the skull highly increases the maximum potential value (by a factor of 11.5 in our case), because of the absence of potential drop in the corresponding volume. The inverse solution without any a priori knowledge indicates that the model with the hole gives the largest errors in both position and dipolar moment. Our results indicate that the resistor mesh model can be used as a robust and user-friendly simulation tool in EEG or event-related potentials. It makes it possible to build up real head models directly from anatomic magnetic resonance imaging without tessellation, and is able to take into account head heterogeneities very simply by changing volume elements conductivity. Hum. Brain Mapping 21:84-95, 2004.

Effects of dipole position, orientation and noise on the accuracy of EEG source localization

BACKGROUND

The electroencephalogram (EEG) reflects the electrical activity in the brain on the surface of scalp. A major challenge in this field is the localization of sources in the brain responsible for eliciting the EEG signal measured at the scalp. In order to estimate the location of these sources, one must correctly model the sources, i.e., dipoles, as well as the volume conductor in which the resulting currents flow. In this study, we investigate the effects of dipole depth and orientation on source localization with varying sets of simulated random noise in 4 realistic head models.

METHODS

Dipole simulations were performed using realistic head models and using the boundary element method (BEM). In all, 92 dipole locations placed in temporal and parietal regions of the head with varying depth and orientation were investigated along with 6 different levels of simulated random noise. Localization errors due to dipole depth, orientation and noise were investigated.

RESULTS

The results indicate that there are no significant differences in localization error due tangential and radial dipoles. With high levels of simulated Gaussian noise, localization errors are depth-dependent. For low levels of added noise, errors are similar for both deep and superficial sources.

CONCLUSION

It was found that if the signal-to-noise ratio is above a certain threshold, localization errors in realistic head models are, on average the same for deep and superficial sources. As the noise increases, localization errors increase, particularly for deep sources.

Mapping of the neuronal networks of human cortical brain functions

OBJECTIVE

The principles and methodology of event-related fMRI, electromagnetic source imaging and intracranial evoked potentials will be described along with some examples of the mapping of the neuronal networks of human cortical brain functions with the use of these techniques.

INTRODUCTION

Functional brain mapping using PET or fMRI has provided clues on the functioning brain and notably on the functional neuroanatomy of cognitive functions. These mapping possibilities can be used to delineate in an individual patient the brain areas subserving a cerebral function that might be compromised by a surgery in a nearby location, or to target a functional neurosurgical procedure.

BACKGROUND

Brain functions and notably "higher brain functions" are served by a complex network of interrelating brain regions. Deeper insights into the functioning of a neuronal network can be gained by adding dynamic, i.e. temporal, information to the functional maps. This will demonstrate the orchestration of the activation of the different brain areas constituting the network, which gives clues to the information processing and therefore to the functioning of the different modules of the network. In order to track the flow of information and the sequential activation of the different brain regions constituting the network, brain activity has to be recorded at the speed of transfer of activation from one neuronal population to the other. The temporal resolution needed to achieve this is not in the range of traditional subtractive or comparative PET or fMRI techniques.

NEW DEVELOPMENTS

Novel fMRI methods that record haemodynamic signal changes after single events (event-related fMRI) are now able to determine sequential neural processing by distinguishing the relative onset-time of activity between different areas. The temporal resolution of event-related (ER) fMRI is sufficient to detect changes of mental activity within the order of several hundreds of milliseconds. This allows the exploration of a broad range of cognitive functions. Nevertheless, this technique is currently not rapid enough to observe the transient coordinations and oscillations of neuronal activities occurring across certain cortical areas during the performance of cognitive tasks. The temporal resolution needed for that is within the order of tens or a few milliseconds and is only accessible by EEG or MEG that allow true real-time measurements of the neuronal activity elicited by a stimulus. Surface recordings of multichannel EEG or MEG combined with novel electromagnetic source localisation algorithms allow a relatively precise estimation of the activated areas. A more direct localisation of electric activity is achieved by intracranial recordings in patients having implanted electrodes for diagnostic reasons. In these cases, a high temporal and spatial resolution is achieved but with a limited sampling of brain regions.

CONCLUSION

Although the temporal resolution of ER fMRI is due to improve, the temporal measures provided by EEG, MEG or intracranial event-related potentials (ERPs) are absolute, which remains a unique feature of these techniques. Therefore, ER fMRI and electromagnetic source imaging are complementary. The maps obtained with ER fMRI may be refined by electromagnetic ERPs that provide further insights into the temporal coordination or orchestration between the cortical areas already detected by ER fMRI and constituting a neuronal network, and ER fMRI can be used to precisely locate the areas coarsely situated and delineated by electromagnetic source imaging. Thus, the combination of ER fMRI and electromagnetic ERPs is essential in order to produce a mapping method with a millimetre spatial resolution and a millisecond temporal resolution. Future applications should combine these techniques to localise precisely and non-invasively relevant sensory, motor and cognitive processes in order to adequately tailor any brain surgery.

Validating the boundary element method for forward and inverse EEG computations in the presence of a hole in the skull

Holes in the skull may have a large influence on the EEG and ERP. Inverse source modeling techniques such as dipole fitting require an accurate volume conductor model. This model should incorporate holes if present, especially when either a neuronal generator or the electrodes are close to the hole, e.g., in case of a trephine hole in the upper part of the skull. The boundary element method (BEM) is at present the preferred method for inverse computations using a realistic head model, because of its efficiency and availability. Using a simulation approach, we have studied the accuracy of the BEM by comparing it to the analytical solution for a volume conductor without a hole, and to the finite difference method (FDM) for one with a hole. Furthermore, we have evaluated the influence of holes on the results of forward and inverse computations using the BEM. Without a hole and compared to the analytical model, a three-sphere BEM model was accurate up to 5-10%, while the corresponding FDM model had an error <0.5%. In the presence of a hole, the difference between the BEM and the FDM was, on average, 4% (1.3-11.4%). The FDM turned out to be very accurate if no hole is present. We believe that the difference between the BEM and the FDM represents the inaccuracy of the BEM. This inaccuracy in the BEM is very small compared to the effect that holes can have on the scalp potential (up to 450%). In regard to the large influence of holes on forward and inverse computations, we conclude that holes in the skull can be treated reliably by means of the BEM and should be incorporated in forward and inverse modeling.

The manual zero potential shifting method in dipole analysis: comparison with neuroimagings in a patient with epilepsy

We previously introduced the manual zero potential shifting (MZPS) method into dipole analysis to reduce the influence by error potential at the analytical stage. The source localizations of epileptic spikes as an equivalent current dipole (ECD) were estimated in a patient with symptomatic epilepsy and contrasted with findings obtained by magnetic resonance imaging (MRI) and single photon emission computed tomography (SPECT). When spikes were analyzed by the MZPS method, ECDs had high values of dipolarity, an indicator of ECD reliability. Moreover, their locations corresponded with lesions shown by MRI and SPECT. When the same spikes were analyzed by the conventional method, dipolarity values were declined and the locations did not correspond with lesions. These results provide further evidence that the MZPS method is of clinical utility in evaluating the electric source generator of epileptic spikes.

Fast realistic modeling in bioelectromagnetism using lead-field interpolation

The practical use of realistic models in bioelectromagnetism is limited by the time-consuming amount of numerical calculations. We propose a method leading to much higher speed than currently available, and compatible with any kind of numerical methods (boundary elements (BEM), finite elements, finite differences). Illustrated with the BEM for EEG and MEG, it applies to ECG and MCG as well. The principle is two-fold. First, a Lead-Field matrix is calculated (once for all) for a grid of dipoles covering the brain volume. Second, any forward solution is interpolated from the pre-calculated Lead-Fields corresponding to grid dipoles near the source. Extrapolation is used for shallow sources falling outside the grid. Three interpolation techniques were tested: trilinear, second-order Bézier (Bernstein polynomials), and 3D spline. The trilinear interpolation yielded the highest speed gain, with factors better than x10,000 for a 9,000-triangle BEM model. More accurate results could be obtained with the Bézier interpolation (speed gain approximately 1,000), which, combined with a 8-mm step grid, lead to intrinsic localization and orientation errors of only 0.2 mm and 0.2 degrees. Further improvements in MEG could be obtained by interpolating only the contribution of secondary currents. Cropping grids by removing shallow points lead to a much better estimation of the dipole orientation in EEG than when solving the forward problem classically, providing an efficient alternative to locally refined models. This method would show special usefulness when combining realistic models with stochastic inverse procedures (simulated annealing, genetic algorithms) requiring many forward calculations.

Accuracy of two dipolar inverse algorithms applying reciprocity for forward calculation

Two inverse algorithms were applied for solving the EEG inverse problem assuming a single dipole as a source model. For increasing the efficiency of the forward computations the lead field approach based on the reciprocity theorem was applied. This method provides a procedure to calculate the computationally heavy forward problem by a single solution for each EEG lead. A realistically shaped volume conductor model with five major tissue compartments was employed to obtain the lead fields of the standard 10-20 EEG electrode system and the scalp potentials generated by simulated dipole sources. A least-squares method and a probability-based method were compared in their performance to reproduce the dipole source based on the reciprocal forward solution. The dipole localization errors were 0 to 9 mm and 2 to 22 mm without and with added noise in the simulated data, respectively. The two different inverse algorithms operated mainly very similarly. The lead field method appeared applicable for the solution of the inverse problem and especially useful when a number of sources, e.g., multiple EEG time instances, must be solved.

Model extraction from magnetic resonance volume data using the deformable pyramid

A general framework for automatic model extraction from magnetic resonance (MR) images is described. The framework is based on a two-stage algorithm. In the first stage, a geometrical and topological multiresolution prior model is constructed. It is based on a pyramid of graphs. In the second stage, a matching algorithm is described. This algorithm is used to deform the prior pyramid in a constrained manner. The topological and the main geometrical properties of the model are preserved, and at the same time, the model adapts itself to the input data. We show that it performs a fast and robust model extraction from image data containing unstructured information and noise. The efficiency of the deformable pyramid is illustrated on a synthetic image. Several examples of the method applied to MR volumes are also represented.

Effects of tissue resistivities on electroencephalogram sensitivity distribution

The effects of tissue resistivities on EEG amplitudes were studied using an anatomically accurate computer model based on the finite difference method (FDM) and lead field analysis covering the whole brain area with 180,000 nodes. Five tissue types and three lead fields were considered for analysis. The changes in sensitivity distribution are directly comparable to changes in the potential distribution on the scalp. The results indicate that a 10% decrease in any tissue resistivity caused 3.0-4.1% differences in the sensitivity distributions of the selected EEG leads. The applied 10% decrease in the resistivity values covers only a fraction of the range of variation of 50% to 100% reported in the literature. The use of a 55% decreased skull resistivity value or a commonly applied three-compartment model increased the differences to 28% and 33%, respectively. In conclusion, both a realistic anatomy and accurate resistivity data are important in EEG head models.

N30 and the effect of explorative finger movements: a model of the contribution of the motor cortex to early somatosensory potentials

OBJECTIVES

The source of the N30 potential in the median nerve somatosensory evoked potentials (SEP) has been previously attributed to a pre-central origin (motor cortex or the supplementary motor area, SMA) or a post-central located generator (somatosensory cortex). This attribution was made from results of lesion studies, the behavior of the potential under pathological conditions, and dipole source localization within spherical volume conductor models.

METHODS

The present study applied dipole source localization and current density reconstruction within individual realistically shaped head models to median nerve SEPs obtained during explorative finger movements.

RESULTS

The SEPs associated with movement of the stimulated hand showed a minor reduction of the N20 amplitude and a markedly reduced amplitude for the frontal N30 and parietal P27, exhibiting a residual frontal negativity around 25 ms. The brain-stem P14 remained unchanged. Mapping of the different SEPs (movement of the non-stimulated hand minus movement of the stimulated hand) showed a bipolar field pattern with a maximum around 30 ms post-stimulus. In eight out of ten normal subjects, both the N30 and the gN30 (subtraction data) sources resided within the pre-central gyrus, more medially than the post-centrally located N20. Two subjects, in contrast, showed rather post-centrally localized sources in this time range. A model of the cortical SEP sources is introduced, explaining the data with respect to previously described findings of dipole localization, and from lesion studies and the alterations seen in motor diseases.

CONCLUSIONS

The results provide evidence for a pre-central N30 generator, predominantly tangentially oriented, located within the motor cortex, while no sources were detected elsewhere. It is suggested that the mechanisms underlying the 'gating' effect during explorative finger movements in the 30 ms time range predominantly arise in the motor cortex.

Accuracy of EEG dipole source localization using implanted sources in the human brain

OBJECTIVES

The location of electrical sources in the brain can be estimated by calculating inverse solutions in which the location, amplitude and orientation of the electrical sources are fitted to the scalp EEG. To assess localization accuracy of the moving dipole inverse solution algorithm (ISA), we studied two patients who had depth electrodes implanted for presurgical planning of epilepsy surgery.

METHODS

Artificial dipoles were created by connecting a single sine wave pulse generator to different pairs of electrodes in multiple orientations and depths. Surface EEG recordings of the resulting pulses were evaluated with the ISA using a 4-shell spherical head model and plotted on the subjects' MRI. Dipole localization errors were evaluated with respect to the number of averaged pulses, different electrode montages and different dipole locations and orientations.

RESULTS

Dipoles located at 40-57 mm from the scalp surface had localization errors that were greater than those located at 62-85 mm. Localization accuracy improved with increasing numbers of pulses and recording electrodes. Results with a standard 10-20 array of 21 electrodes showed an average localization error of 17 mm, whereas 41 electrodes improved this to 13 mm. Mean angular errors were 31 and 30 degrees, respectively.

CONCLUSIONS

The ISA was able to differentiate between tangential and radial dipoles. We conclude that our implementation of the ISA is a useful and sound method for localizing electrical activity in the brain.

Combined mapping of human auditory EEG and MEG responses

Auditory electric and magnetic P50(m), N1(m) and MMN(m) responses to standard, deviant and novel sounds were studied by recording brain electrical activity with 25 EEG electrodes simultaneously with the corresponding magnetic signals measured with 122 MEG gradiometer coils. The sources of these responses were located on the basis of the MEG responses; all were found to be in the supratemporal plane. The goal of the present paper was to investigate to what degree the source locations and orientations determined from the magnetic data account for the measured EEG signals. It was found that the electric P50, N1 and MMN responses can to a considerable degree be explained by the sources of the corresponding magnetic responses. In addition, source-current components not detectable by MEG were shown to contribute to the measured EEG signals.

Mapping epileptic foci by the dipole tracing method in a brain tumor patient with olfactory seizures: comparison with intraoperative electrocorticograms

We estimated the position of the epileptic foci in a case of brain tumor with olfactory seizures using the Dipole Tracing Method (DTM) and compared the results with electrocorticograms (ECoGs) recorded during surgical resection. The case was a 24-year-old male. Electroencephalograms (EEG) showed frequent focal spikes in the right temporal area. Magnetic resonance imaging revealed a tumor in the right hippocampus region. We analyzed the spikes using DTM with a CDT-1000 EEG analyzer. The locations of two independent foci were analyzed; one was thought to be in the right hippocampus and the other in the right superior temporal gyrus. When the ECoG was taken, the results were in very close correlation with those of DTM, demonstrating the accuracy of DTM in the estimation of the location of epileptic foci in epileptic seizures with brain lesions.

Differential effects of normal aging on sources of standard N1, target N1 and target P300 auditory event-related brain potentials revealed by low resolution electromagnetic tomography (LORETA)

The P300 event-related potential (ERP) is considered to be closely related to cognitive processes. In normal aging, P300 scalp latencies increase, parietal P300 scalp amplitudes decrease and the scalp potential field shifts to a relatively more frontal distribution. Based on ERPs recorded in 172 normal healthy subjects aged between 20 and 88 years in an auditory oddball paradigm, the effects of age on the electrical activity in the brain corresponding to N1 and P300 components were estimated by means of low resolution electromagnetic tomography (LORETA). This distributed approach directly computes a unique 3-dimensional electrical source distribution by assuming that neighbouring neurons are simultaneously and synchronously active. N1 LORETA generators, located predominantly in both auditory cortices and also symmetrically in prefrontal areas, increased with advancing age for standards but remained stable for targets. P300 LORETA generators, located symmetrically in the prefrontal cortex, in the parieto-occipital junction and in the inferior parietal cortex (supramarginal gyrus) and medially in the superior parietal cortex, were differentially affected by age. While age did not affect parieto-occipital sources, superior parietal and right prefrontal sources decreased pronouncedly. Thus, in normal aging, P300 current density decreased in regions were a fronto-parietal network for sustained attention was localized.

The cortical somatotopic map and phantom phenomena in subjects with congenital limb atrophy and traumatic amputees with phantom limb pain

The extent of the cortical somatotopic map and its relationship to phantom phenomena was tested in five subjects with congenital absence of an upper limb, four traumatic amputees with phantom limb pain and five healthy controls. Cortical maps of the first and fifth digit of the intact hand, the lower lip and the first toe (bilaterally) were obtained using neuroelectric source imaging. The subjects with congenital upper limb atrophy showed symmetric positions of the left and right side of the lower lip and the first toe, whereas the traumatic amputees with pain showed a significant shift (about 2.4 cm) of the cortical representation of the lower lip towards the hand region contralateral to the amputation side but no shift for the toe representation. In healthy controls, no significant hemispheric differences between the cortical representation of the digits, lower lip or first toe were found. Phantom phenomena were absent in the congenital but extensive in the traumatic amputees. These data confirm the assumption that congenital absence of a limb does not lead to cortical reorganization or phantom limbs whereas traumatic amputations that are accompanied by phantom limb pain show shifts of the cortical areas adjacent to the amputation zone towards the representation of the deafferented body part.

Initial estimation methods for dipole modeling in localization of epileptogenic focus

Although great sensitivities to initial estimates is an inherent feature of iterative dipole optimization algorithms, the study of better initial estimates has been neglected. For convergence to a correct solution, the initial estimates should be extremely close to the desired solution and be attributed to only a single dipole focus. To alleviate the interference of background and multiple foci, the singular value decomposition (SVD) technique is used initially to extract the dominant component of the EEG spike for dipole localization. By observing the three-dimensional topographic mapping, the initial estimates of the dipole parameter set can be computed from the intersection between the null potential plane and from the peak and valley potentials. This work also compares initial estimations of simulation data, including noisy data, noisy data with SVD process and noise-free data. Experimental results confirm that good initial estimates for the dipole parameters are necessary to ensure rapid convergence to the correct solution.

Views on how the electrical activity that the brain generates reflects the functions of different language structures

Human language is what it is because of its function and its implementation. We are far from understanding how language comprehension is carried out by the human brain. This task can be made easier by considering that evidence for the what and how of language comes from the study of linguistics, psychology, and neuroscience. The approach outlined herein describes how these different sources of evidence can be combined in studies of written and spoken sentence processing by using a measure of the brain's electrical activity. The outcome is a more temporally precise view of the analysis of language structures in our minds and brains.

A systematic evaluation of the spherical model accuracy in EEG dipole localization

This paper presents a study of the intrinsic localization error bias due to the use of a spherical geometry model on EEG simulated data obtained from realistically shaped models. About 2000 dipoles were randomly chosen on the segmented cortex surface of a particular subject. Forward calculations were performed using a uniformly meshed model for each dipole located at a depth greater than 20 mm below the brain surface, and locally refined models were used for shallower dipoles. Inverse calculations were performed using four different spherical models and another uniformly meshed model. It was found that the best spherical model lead to localization errors of 5-6 mm in the upper part of the head, and of 15-25 mm in the lower part. The influence of the number of electrodes upon this intrinsic bias was also studied. It was found that using 32 electrodes instead of 19 improves the localization by 2.7 mm on average, while using 63 instead of 32 electrodes lead to improvements of less than 1 mm. Finally, simulations involving two simultaneously active dipoles (one in the vicinity of each auditory cortex) show localization errors increasing by about 2-3 mm.