Localization of a dipolar source in a skull phantom: realistic versus spherical model

Menninghaus, E.; Lütkenhöner, Bernd; Gonzalez, Sara

doi:10.1109/10.324531

Cited by 42 publications

(19 citation statements)

References 7 publications

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“…This model is certainly a considerable simplification of the true situation. The effect of an inappropriate volume conductor model can be assessed from Menninghaus et al [1994]. Since the estimated sources were located relatively superficially, the error made by choosing a homogeneous sphere as the volume conductor is presumably not greater than a few millimeters, and it can be assumed that all estimated source locations are effected in basically the same systematic way.…”

Section: General Methodological Considerationsmentioning

confidence: 99%

High-Precision Neuromagnetic Study of the Functional Organization of the Human Auditory Cortex

1998

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Previous studies have proven that a dipole source analysis of the auditory evoked field is capable of providing evidence of the tonotopic organization of the human auditory cortex. To explore the nature of the estimated dipoles in greater detail, a single subject was extensively studied, and the estimated sources were registered in a three-dimensional reconstruction of the cortical surface derived from magnetic resonance images. The stimuli were 500-ms tone bursts with frequencies of 250, 500, 1,000, and 2,000 Hz (mean intensity of 60 dB SL). The total number of stimuli presented per condition was about 3,600 (36 independent experiments spread over 4 days). Using special postprocessing techniques, the relative localization accuracy could be enhanced to such an extent that differences in the dipole locations of 1 mm could be clearly distinguished. The results suggest that peak N1m (latency around 100 ms) arises from the planum temporale, whereas peak P2m (latency around 170 ms) appears to correspond to a center of activity in (or close to) Heschl’s gyrus. The tonotopic organization found for the generator of N1m was consistent with earlier studies (‘the higher the frequency the deeper the source’). However, additional findings (time dependence of the estimated sources; slightly different tonotopy obtained for field change; dependence of the estimated sources on the estimation technique) indicate that multiple areas are involved in the generation of N1m. Evidence of a frequency-dependent source location was found also for P2m.

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Section: General Methodological Considerationsmentioning

confidence: 99%

High-Precision Neuromagnetic Study of the Functional Organization of the Human Auditory Cortex

1998

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“…This strategy has a drawback, however, because the accuracy of the numerical computation is directly dependent on the mesh density, as has been evaluated using the boundary element method [Fuchs et al, 1998;Menninghaus et al, 1994;Roth et al, 1993;Yvert et al, 1995Yvert et al, , 1996Zanow and Peters, 1995;] or the finite element method . Fletcher et al [1995] have proposed a variant formulation of the BEM using the reciprocity theorem to increase the speed of realistic models in EEG, which cannot be as efficiently used in MEG.…”

Section: Introductionmentioning

confidence: 99%

Fast realistic modeling in bioelectromagnetism using lead‐field interpolation

Yvert

Cheylus

Pernier

2001

Human Brain Mapping

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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.

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“…Phantom studies have reported localization accuracy for EEG of 7-8 mm [Leahy et al, 1998] and for MEG of 2-4 mm [Gharib et al, 1995;Leahy et al, 1998;Menninghaus et al, 1994]. The localization superiority of MEG over EEG is less obvious in data from measurements made in patients.…”

Section: Introductionmentioning

confidence: 99%

Monte Carlo simulation studies of EEG and MEG localization accuracy

Liu¹,

Dale²,

Belliveau³

2002

Human Brain Mapping

330

256

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Both electroencephalography (EEG) and magnetoencephalography (MEG) are currently used to localize brain activity. The accuracy of source localization depends on numerous factors, including the specific inverse approach and source model, fundamental differences in EEG and MEG data, and the accuracy of the volume conductor model of the head (i.e., the forward model). Using Monte Carlo simulations, this study removes the effect of forward model errors and theoretically compares the use of EEG alone, MEG alone, and combined EEG/MEG data sets for source localization. Here, we use a linear estimation inverse approach with a distributed source model and a realistic forward head model. We evaluated its accuracy using the crosstalk and point spread metrics. The crosstalk metric for a specified location on the cortex describes the amount of activity incorrectly localized onto that location from other locations. The point spread metric provides the complementary measure: for that same location, the point spread describes the mis-localization of activity from that specified location to other locations in the brain. We also propose and examine the utility of a "noise sensitivity normalized" inverse operator. Given our particular forward and inverse models, our results show that 1) surprisingly, EEG localization is more accurate than MEG localization for the same number of sensors averaged over many source locations and orientations; 2) as expected, combining EEG with MEG produces the best accuracy for the same total number of sensors; 3) the noise sensitivity normalized inverse operator improves the spatial resolution relative to the standard linear estimation operator; and 4) use of an a priori fMRI constraint universally reduces both crosstalk and point spread. Hum. Brain Mapping 16:47-62, 2002.

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Localization of a dipolar source in a skull phantom: realistic versus spherical model

Cited by 42 publications

References 7 publications

High-Precision Neuromagnetic Study of the Functional Organization of the Human Auditory Cortex

High-Precision Neuromagnetic Study of the Functional Organization of the Human Auditory Cortex

Fast realistic modeling in bioelectromagnetism using lead‐field interpolation

Monte Carlo simulation studies of EEG and MEG localization accuracy

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