High resolution EEG: a new model-dependent spatial deblurring method using a realistically-shaped MR-constructed subject's head model

Babiloni, Fabio; Babiloni, Claudio; Carducci, Filippo; Fattorini, Luigi; Anello, C.; Onorati, Paolo; Urbano, Antonio

doi:10.1016/s0921-884x(96)96508-x

Cited by 112 publications

(76 citation statements)

References 39 publications

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“…On the other hand, if the number of ECDs used in the dipole source localization is not correct, then misleading results maybe obtained. For this reason, distributed source imaging approaches that do not require a priori knowledge on the number of source dipoles have been investigated (Hamalainen & Ilmoniemi, 1984;Dale & Sereno, 1993;Gevins et al, 1994;Pascual-Marqui et al, 1994;Babiloni et al, 1997Babiloni et al, ,2001He et al, 1999He et al, ,2001He et al, ,2002aHe et al, , 2002bZhang et al, 2003). Therefore, development of methods being able to estimate reliably the number of source dipoles is of importance for further enhancing dipole source localization and ultimate improving our ability to image and localize brain electrical sources from noninvasive electromagnetic measurements.…”

Section: Discussionmentioning

confidence: 99%

On the estimation of the number of dipole sources in EEG source localization

Xiang¹,

He²

2005

Clinical Neurophysiology

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Background-The purpose of the present study was to determine the number of the equivalent dipole sources corresponding to the scalp EEG using the information criterion method based on the instantaneous-state modeling.Methods-A three-concentric-spheres head model was used to represent the head volume conductor. The Powell algorithm was used to solve the inverse problem of estimating the equivalent dipoles from the scalp EEG. The information criterion with different penalty functions was used to determine the dipole number. Computer simulations were conducted to evaluate effects of various parameters on the estimation of dipole number.Results-The present results suggest that the present method is able to estimate the number of equivalent current dipoles (ECDs) from instantaneous scalp EEG measurements, and that increase in the electrode number can improve the accuracy of estimation of the ECD number. For two ECDs, the best performance of estimation with 20% white noise were 85%, 92% and 94%, when 64, 128 and 256 electrodes are used, respectively. When there are 3 ECDs, the present results suggest that using 256 electrodes gave up to 82% estimation accuracy. The present simulation results also indicate that the accuracies of identification are similar when the minimum distance between dipoles is either 1 or 2 cm, which was used in the simulation. It was also found that the different penalty functions used in the information criterion method could have substantial influence on the estimation accuracy.Conclusions-The present method can estimate the number of ECDs from instantaneous scalp EEG distribution for up to three dipoles.Significance-The successful estimation of the number of ECDs will play an important role in expanding the applicability of dipole source localization to multiple sources.

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Section: Discussionmentioning

confidence: 99%

On the estimation of the number of dipole sources in EEG source localization

Xiang¹,

He²

2005

Clinical Neurophysiology

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“…In the inhomogeneous spherical source-conductor model, the radii of the brain, the skull, and the scalp spheres were taken as 0.87, 0.92, and 1.0, respectively [6], [11], [26]. The normalized conductivity of the scalp and the brain was taken as σ 0 = 1.0, and that of the skull as σ s = 0.0125.…”

Section: Simulationmentioning

confidence: 99%

Signal and Noise Covariance Estimation Based on ICA for High-Resolution Cortical Dipole Imaging

Hori

Sunaga

Watanabe

2010

IEICE Trans. Inf. & Syst.

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SUMMARYWe investigated suitable spatial inverse filters for cortical dipole imaging from the scalp electroencephalogram (EEG). The effects of incorporating statistical information of signal and noise into inverse procedures were examined by computer simulations and experimental studies. The parametric projection filter (PPF) and parametric Wiener filter (PWF) were applied to an inhomogeneous three-sphere volume conductor head model. The noise covariance matrix was estimated by applying independent component analysis (ICA) to scalp potentials. The present simulation results suggest that the PPF and the PWF provided excellent performance when the noise covariance was estimated from the differential noise between EEG and the separated signal using ICA and the signal covariance was estimated from the separated signal. Moreover, the spatial resolution of the cortical dipole imaging was improved while the influence of noise was suppressed by including the differential noise at the instant of the imaging and by adjusting the duration of noise sample according to the signal to noise ratio. We applied the proposed imaging technique to human experimental data of visual evoked potential and obtained reasonable results that coincide to physiological knowledge.

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“…With resistive model of the head, the information given by electroencephalography (EEG) can be effectively processed [1], [2], [3]. Models can be applied to the simulation of electric fields inside the head.…”

Section: Introductionmentioning

confidence: 99%

The conductivity of brain tissues: comparison of results in vivo and in vitro measurements

Latikka

Hyttinen

Kuurne³

et al.

2001 Conference Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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Abstract-Electric properties of tissues depend on many factors, including measurement frequency and temperature. Properties differ also in vivo and in vitro situations. We have collected conductivity values from several studies and compared the values measured from living tissue and tissue samples. The results show that the resistivity ratio of grey and white matter increases 36% after death, and the resistivity values increase over 100%. Keywords -Conductivity, brain tissue, source location I. INTRODUCTIONThe electric properties of tissues have a very important role in biomedical engineering. These properties determine the electrical current pathways through human body. If these properties are known, electrical models can be constructed, for example, to represent the electrical activation of the heart or the conduction of the brain activity to the scalp surface.With resistive model of the head, the information given by electroencephalography (EEG) can be effectively processed [1], [2], [3]. Models can be applied to the simulation of electric fields inside the head. For example, an electric source (dipole or set of dipoles) can be inserted inside the model and thereafter the electric field distribution can be computed. Further, the measured EEG signal can be used for obtaining the source location in the volume conductor. For example, epileptic loci can be located. In principal, accuracy of these computations is dependent on the accuracy of the volume conductor i.e. the number of compartments and their conductivities [4]. In [5] the results indicated that a 10% decrease in tissue resisitivity cause 3.0 -4.1% differences in the sensitivity distributions of the selected 3 EEG leads. In modeling the important factor is the ratio between various conductivities. The ratio of skull and brain resistivites is 15:1 rather than the commonly used ratio of 80:1 [6]. In [7] the estimated resistivity ratio of skull and brain is 14:1.There have been recent advances in source localization techniques. The amount of electrodes in EEG studies has been increased. Instead of the traditional 21 electrode 10-20 system, 64 or more electrodes are usually used. In some studies even 512 electrodes are utilized. This improves the spatial accuracy, thus giving more information about brain functions. However, most researchers continue to take conductivity parameters from standard references [8], [9]. The standard reference values are usually measured from tissue samples. An increase in tissue resistivity with time after death has been reported in [8], [10]. Literature values are also measured at much higher frequencies than EEG frequencies. II. METHODOLOGYPreviously we have made in vivo resistivity measurements with needle electrode from 9 patients with brain tumors [11]. Due to the location of tumors and selected surgical paths, it was not possible to measure both grey and white matters with every patient. The number of measurements ranged from 1 to 13 for each tissue measured.In addition to our own in vivo measurements [11], resistivity val...

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High resolution EEG: a new model-dependent spatial deblurring method using a realistically-shaped MR-constructed subject's head model

Cited by 112 publications

References 39 publications

On the estimation of the number of dipole sources in EEG source localization

On the estimation of the number of dipole sources in EEG source localization

Signal and Noise Covariance Estimation Based on ICA for High-Resolution Cortical Dipole Imaging

The conductivity of brain tissues: comparison of results in vivo and in vitro measurements

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