Biomedical subjects

Jens Haueisen

Publications and source records attributed to Jens Haueisen.

At least 19 recordsLinked to original sources

PubMed2006

Alpha entrainment in human electroencephalogram and magnetoencephalogram recordings.

Visual stimulation by repetitive flashes of light can lead to an entrainment of the alpha rhythm in electroencephalogram recordings (also called photic driving). We report a comparison of simultaneously recorded electric and magnetic data in a photic driving experiment, adapted to the individual alpha rhythm of 10 healthy volunteers. We show that there is a stronger frequency entrainment in magnetoencephalogram than in electroencephalogram recordings in all volunteers, which indicates a possible tangential brain activity underlying the dominant entrainment effect. The entrainment in the magnetoencephalogram lasts over significantly more frequencies and is most effective in the region around the individual alpha and a half alpha. For different channels, we found different degrees of entrainment showing topological and time-varying properties.

Adult↗

PubMed2006

Influence of head models on neuromagnetic fields and inverse source localizations.

BACKGROUND: The magnetoencephalograms (MEGs) are mainly due to the source currents. However, there is a significant contribution to MEGs from the volume currents. The structure of the anatomical surfaces, e.g., gray and white matter, could severely influence the flow of volume currents in a head model. This, in turn, will also influence the MEGs and the inverse source localizations. This was examined in detail with three different human head models. METHODS: Three finite element head models constructed from segmented MR images of an adult male subject were used for this study. These models were: (1) Model 1: full model with eleven tissues that included detailed structure of the scalp, hard and soft skull bone, CSF, gray and white matter and other prominent tissues, (2) the Model 2 was derived from the Model 1 in which the conductivity of gray matter was set equal to the white matter, i.e., a ten tissuetype model, (3) the Model 3 consisted of scalp, hard skull bone, CSF, gray and white matter, i.e., a five tissue-type model. The lead fields and MEGs due to dipolar sources in the motor cortex were computed for all three models. The dipolar sources were oriented normal to the cortical surface and had a dipole moment of 100 microA meter. The inverse source localizations were performed with an exhaustive search pattern in the motor cortex area. A set of 100 trial inverse runs was made covering the 3 cm cube motor cortex area in a random fashion. The Model 1 was used as a reference model. RESULTS: The reference model (Model 1), as expected, performed best in localizing the sources in the motor cortex area. The Model 3 performed the worst. The mean source localization errors (MLEs) of the Model 3 were larger than the Model 1 or 2. The contour plots of the magnetic fields on top of the head were also different for all three models. The magnetic fields due to source currents were larger in magnitude as compared to the magnetic fields of volume currents. DISCUSSION: These results indicate that the complexity of head models strongly influences the MEGs and the inverse source localizations. A more complex head model performs better in inverse source localizations as compared to a model with lesser tissue surfaces.

Action Potentials↗

PubMed2006

Influence of head models on EEG simulations and inverse source localizations.

BACKGROUND: The structure of the anatomical surfaces, e.g., CSF and gray and white matter, could severely influence the flow of volume currents in a head model. This, in turn, will also influence the scalp potentials and the inverse source localizations. This was examined in detail with four different human head models. METHODS: Four finite element head models constructed from segmented MR images of an adult male subject were used for this study. These models were: (1) Model 1: full model with eleven tissues that included detailed structure of the scalp, hard and soft skull bone, CSF, gray and white matter and other prominent tissues, (2) the Model 2 was derived from the Model 1 in which the conductivity of gray matter was set equal to the white matter, i.e., a ten tissue-type model, (3) the Model 3 was derived from the Model 1 in which the conductivities of gray matter and CSF were set equal to the white matter, i.e., a nine tissue-type model, (4) the Model 4 consisted of scalp, hard skull bone, CSF, gray and white matter, i.e., a five tissue-type model. How model complexity influences the EEG source localizations was also studied with the above four finite element models of the head. The lead fields and scalp potentials due to dipolar sources in the motor cortex were computed for all four models. The inverse source localizations were performed with an exhaustive search pattern in the motor cortex area. The inverse analysis was performed by adding uncorrelated Gaussian noise to the scalp potentials to achieve a signal to noise ratio (SNR) of -10 to 30 dB. The Model 1 was used as a reference model. RESULTS: The reference model, as expected, performed the best. The Model 3, which did not have the CSF layer, performed the worst. The mean source localization errors (MLEs) of the Model 3 were larger than the Model 1 or 2. The scalp potentials were also most affected by the lack of CSF geometry in the Model 3. The MLEs for the Model 4 were also larger than the Model 1 and 2. The Model 4 and the Model 3 had similar MLEs in the SNR range of -10 dB to 0 dB. However, in the SNR range of 5 dB to 30 dB, the Model 4 has lower MLEs as compared with the Model 3. DISCUSSION: These results indicate that the complexity of head models strongly influences the scalp potentials and the inverse source localizations. A more complex head model performs better in inverse source localizations as compared to a model with lesser tissue surfaces. The CSF layer plays an important role in modifying the scalp potentials and also influences the inverse source localizations. In summary, for best results one needs to have highly heterogeneous models of the head for accurate simulations of scalp potentials and for inverse source localizations.

Adult↗

PubMed2006

Influence of anisotropic conductivity on EEG source reconstruction: investigations in a rabbit model.

The aim of our work was to quantify the influence of white matter anisotropic conductivity information on electroencephalography (EEG) source reconstruction. We performed this quantification in a rabbit head using both simulations and source localization based on invasive measurements. In vivo anisotropic (tensorial) conductivity information was obtained from magnetic resonance diffusion tensor imaging and included into a high-resolution finite-element model. When neglecting anisotropy in the simulations, we found a shift in source location of up to 1.3 mm with a mean value of 0.3 mm. The averaged orientational deviation was 10 degree and the mean magnitude error of the dipole was 29%. Source localization of the first cortical components after median and tibial nerve stimulation resulted in anatomically verified dipole positions with no significant anisotropy effect. Our results indicate that the expected average source localization error due to anisotropic white matter conductivity is within the principal accuracy limits of current inverse procedures. However, larger localization errors might occur in certain cases. In contrast, dipole orientation and dipole strength are influenced significantly by the anisotropy. We conclude that the inclusion of tissue anisotropy information improves source estimation procedures.

Algorithms↗

PubMed2006

Estimating parametric line-source models with electroencephalography.

We develop three parametric models for electroencephalography (EEG) to estimate current sources that are spatially distributed on a line. We assume a realistic head model and solve the EEG forward problem using the boundary element method (BEM). We present the models with increasing degrees of freedom, provide the forward solutions, and derive the maximum-likelihood estimates as well as Cramér-Rao bounds of the unknown source parameters. A series of experiments are conducted to evaluate the applicability of the proposed models. We use numerical examples to demonstrate the usefulness of our line-source models in estimating extended sources. We also apply our models to the real EEG data of N20 response that is known to have an extended source. We observe that the line-source models explain the N20 measurements better than the dipole model.

Action Potentials↗

PubMed2006

Surface-source modeling and estimation using biomagnetic measurements.

We propose a number of electric source models that are spatially distributed on an unknown surface for biomagnetism. These can be useful to model, e.g., patches of electrical activity on the cortex. We use a realistic head (or another organ) model and discuss the special case of a spherical head model with radial sensors resulting in more efficient computations of the estimates for magnetoencephalography. We derive forward solutions, maximum likelihood (ML) estimates, and Cramér-Rao bound (CRB) expressions for the unknown source parameters. A model selection method is applied to decide on the most appropriate model. We also present numerical examples to compare the performances and computational costs of the different models and illustrate when it is possible to distinguish between surface and focal sources or line sources. Finally, we apply our methods to real biomagnetic data of phantom human torso and demonstrate the applicability of them.

Action Potentials↗

PubMed2006

Parametric surface-source modeling and estimation with electroencephalography.

Electroencephalography (EEG) is an important tool for studying the brain functions and is becoming popular in clinical practice. In this paper, we develop four parametric EEG models to estimate current sources that are spatially distributed on a surface. Our models approximate the source shape and extent explicitly and can be applied to localize extended sources which are often encountered, e.g., in epilepsy diagnosis. We assume a realistic head model and solve the EEG forward problem using the boundary element method. We present the source models with increasing degrees of freedom, provide the forward solutions, and derive the maximum-likelihood estimates as well as Cramér-Rao bounds of the unknown source parameters. In order to evaluate the applicability of the proposed models, we first compare their estimation performances with the dipole model's using several known source distributions. We then discuss the conditions under which we can distinguish between the proposed extended sources and the focal dipole using the generalized likelihood ratio test. We also apply our models to the electric measurements obtained from a phantom body in which an extended electric source is imbedded. We observe that the proposed model can capture the source extent information satisfactorily and the localization accuracy is better than the dipole model.

Action Potentials↗

PubMed2006

Low HRV entropy is strongly associated with myocardial infarction.

Heart rate variability (HRV) is a marker of autonomous activity in the heart. An important application of HRV measures is the stratification of mortality risk after myocardial infarction. Our hypothesis is that the information entropy of HRV, a non-linear approach, is a suitable measure for this assessment. As a first step, to evaluate the effect of myocardial infarction on the entropy, we compared the entropy to standard HRV parameters. The entropy was estimated by compressing the tachogram with Bzip2. For univariate comparison, statistical tests were used. Multivariate analysis was carried out using automatically generated decision trees. The classification rate and the simplicity of the decision trees were the two evaluation criteria. The findings support our hypothesis. The meanNN-normalized entropy is reduced in patients with myocardial infarction with very high significance. One entropy parameter alone exceeds the discrimination strength of multivariate standards-based trees.

Algorithms↗

PubMed2006

Spatiotemporal correlation analyses: a new procedure for standardisation of DC magnetocardiograms.

There is a lack of standard methods for the analysis of magnetocardiograms (MCGs). MCG signals have a shape similar to the ECG (P wave, QRS complex, T wave). High-quality multichannel recordings can indicate even slight disturbances of de- and repolarisation. The purpose of our study was to apply a new approach in the analysis of signal-averaged DC-MCGs. DC-MCGs (31-channel) were recorded in 182 subjects: 110 patients after myocardial infarction and 72 controls. Spatiotemporal correlation analysis of the QRS complex and T wave patterns throughout the entire heart cycle was used to analyse homogeneity of de- and repolarisation. These plots were compared to standard ECG analyses (electrical axis, Q wave, ST deviation, T polarity and shape). Spatiotemporal correlation analyses seem to be applicable in assessing the course of electrical repolarisation with respect to homogeneity. MCG provided all diagnostic information contained in common ECG recordings at high significance levels. The ECG patterns were included in 5/8 of our parameters for electrical axis, 6/8 for Q-wave, 7/8 for ST deviation and 5/8 for T-polarity based on two time series of correlation coefficients. We conclude that our spatiotemporal correlation approach provides a new tool for standardised analysis of cardiac mapping data such as MCG.

Algorithms↗

PubMed2005

Passive vortex currents in magneto- and electrocardiography: comparison of magnetic and electric signal strengths.

Vortex currents may be of importance in the early diagnosis of myocardial infarction caused by an occlusion of a coronary artery. We investigated the influence of a passive vortex current distribution, modelled by different conductivities in a hollow cylinder, on the localization error and on the signal strength in both the magnetocardiogram and the electrocardiogram. The hollow cylinder was mounted in a realistically shaped physical torso phantom. A platinum dipole was inserted into the cylinder. The compartment boundaries were modelled with two special ionic exchange membranes. The conductivity ratio of the cylinder compartment to the torso compartment was varied from 0.25 to 100. We compared the simultaneously measured magnetic and electric signal strengths as a function of this conductivity ratio. We found that an increasing conductivity ratio causes only a slight increase (about 19%) of the magnetic signal strength but a strong decrease (about 81%) of the electric signal strength. Using a homogeneous torso model, the dipole localization errors were, depending on the conductivity ratio, up to 16 mm. In conclusion, passive vortex currents might partially explain the differences between magnetocardiographic and electrocardiographic recordings observed both experimentally and clinically.

Body Surface Potential Mapping↗

PubMed2005

Time-frequency filtering of MEG signals with matching pursuit.

Time-frequency signal analysis based on various decomposition techniques is widely used in biomedical applications. Matching Pursuit is a new adaptive approach for time-frequency decomposition of such biomedical signals. Its advantage is that it creates a concise signal approximation with the help of a small set of Gabor atoms chosen iteratively from a large and redundant set. In this paper, the usage of Matching Pursuit for time-frequency filtering of biomagnetic signals is proposed. The technique was validated on artificial signals and its performance was tested for varying signal-to-noise ratios using both simulated and real MEG somatic evoked magnetic field data.

Algorithms↗

PubMed2005

Perception of phrase structure in music.

Neither music nor spoken language form uniform auditory streams, rather, they are structured into phrases. For the perception of such structures, the detection of phrase boundaries is crucial. We discovered electroencephalography (EEG) and magnetoencephalography (MEG) correlates for the perception of phrase boundaries in music. In EEG, this process was marked by a positive wave approximately between 500 and 600 ms after the offset of a phrase boundary with a centroparietal maximum. In MEG, we found major activity in an even broader time window (400-700 ms). Source localization revealed that likely candidates for the generation of the observed effects are structures in the limbic system, including anterior and posterior cingulate as well as posterior mediotemporal cortex. The timing and topography of the EEG effect bear some resemblance to a positive shift (closure positive shift, CPS) found for prosodic phrase boundaries during speech perception in an earlier study, suggesting that the underlying processes might be related. Because the brain structures, which possibly underlie the observed effects, are known to be involved in memory and attention processes, we suggest that the CPS may not reflect the detection of the phrase boundary as such, but those memory and attention related processes that are necessary to guide the attention focus from one phrase to the next, thereby closing the former and opening up the next phrase.

Adult↗

PubMed2005

Prenatal diagnosis of a long QT syndrome by fetal magnetocardiography in an unshielded bedside environment.

OBJECTIVE: The potentially life threatening long QT syndrome should be diagnosed during pregnancy to improve perinatal care. METHODS: A patient with a family history for a hereditary long QT syndrome presented at 30 weeks of her first pregnancy with fetal bradycardia and a narrow oscillation bandwidth on cardiotocography without structural abnormalities of the fetal heart. Fetal magnetocardiography was performed with a prototype biomagnetometer/gradiometer device in a magnetically unshielded environment. The cardiac time intervals were determined in the averaged PQRST complex. RESULTS: The QT time and the frequency-corrected QTc showed a marked prolongation to 380 ms and 0.52 s, respectively. The findings were confirmed in the postnatal electrocardiogram after spontaneous term delivery in a perinatal center. The causative mutation on chromosome 11 had been passed on to the newborn from his mother. CONCLUSION: Bedside fetal magnetocardiography revealed the exact diagnosis of the long QT syndrome in a period of the gestation when the fetus was electrically isolated by the vernix caseosa that hinders electrocardiography. To patients at risk of fetal cardiac abnormalities, magnetocardiography can be offered as a non-invasive diagnostic bedside procedure. The diagnosis should trigger closer surveillance and delivery in a perinatal center.

Adult↗

PubMed2005

Vortex shaped current sources in a physical torso phantom.

Recent studies reported differential information in human magnetocardiogram and in electrocardiogram. Vortex currents have been discussed as a possible source of this divergence. With the help of physical phantom experiments, we quantified the influence of active vortex currents on the strength of electric and magnetic signals, and we tested the ability of standard source localization algorithms to reconstruct vortex currents. The active vortex currents were modeled by a set of twelve single current dipoles arranged in a circle and mounted inside a phantom that resembles a human torso. Magnetic and electric data were recorded simultaneously while the dipoles were switched on stepwise one after the other. The magnetic signal strength increased continuously for an increasing number of dipoles switched on. The electric signal strength increased up to a semicircle and decreased thereafter. Source reconstruction with unconstrained focal source models performed well for a single dipole only (less than 3-mm localization error). Minimum norm source reconstruction yielded reasonable results only for a few of the dipole configurations. In conclusion active vortex currents might explain, at least in part, the difference between magnetically and electrically acquired data, but improved source models are required for their reconstruction.

Action Potentials↗

PubMed2005

Evaluation of the distortion of EEG signals caused by a hole in the skull mimicking the fontanel in the skull of human neonates.

OBJECTIVE: Interpretation of Electroencephalography (EEG) signals from newborns is in some cases difficult because the fontanels and open sutures produce inhomogeneity in skull conductivity. We experimentally determined how EEG is influenced by a hole mimicking the anterior fontanel since distortion of EEG signals is important in neurological examinations during the perinatal period. METHODS: Experiments were carried out on 10 anesthetized farm swine. The fontanel was mimicked by a hole (12 x 12 mm) in the skull. The hole was filled with 3 types of medium differing in conductivity (air, 0 S/m; sucrose-agar, 0.017 S/m; saline-agar, 1.28 S/m). Three positions of the snout were stimulated with a concentric bipolar electrode to activate cortical areas near the middle, the edge, and the outside of the hole. The somatic-evoked potential (SEP) was recorded by a 4 x 4 electrode array with a 4mm grid spacing. It was placed on the 4 quadrants of a 28 x 28 mm measurement area on a saline-soaked filter paper over the skull, which served as artificial scalp. RESULTS: The SEP over the hole was clearly stronger when the hole was filled with sucrose- or saline-agar as compared to air, although paradoxically the leakage current was stronger for the sucrose- than saline-agar. The current leaking from the hole was strongly related to position of the active tissue. It was nearly negligible for sources 6-10 mm away from the border of the hole. The distortion was different for 3 components of the SEP elicited by each stimulus, probably indicating effects of source distance relative to the hole. CONCLUSIONS: EEG is strongly distorted by the presence of a hole/fontanel with the distortion specifically dependent on both conductivity of the hole and source location. SIGNIFICANCE: The distortion of the EEG is in contrast to the lack of distortion of magnetoencephalography (MEG) signals shown by previous studies. In studying brain development with EEG, the infant's head and sources should be modeled accurately in order to relate the signals to the underlying activity. MEG may be particularly advantageous over EEG for studying brain functions in infants since it is relatively insensitive to skull defects.

Animals↗

PubMed2005

Line-source modeling and estimation with magnetoencephalography.

We propose a number of source models that are spatially distributed on a line for magnetoencephalography (MEG) using both a spherical head with radial sensors for more efficient computation and a realistic head model for more accurate results. We develop these models with increasing degrees of freedom, derive forward solutions, maximum-likelihood (ML) estimates, and Cramér-Rao bound (CRB) expressions for the unknown source parameters. A model selection method is applied to select the most appropriate model. We also present numerical examples to compare the performances and computational costs of the different models, to determine the regions where better estimates are possible and when it is possible to distinguish between line and focal sources. We demonstrate the usefulness of the proposed line-source models over the previously available focal source model in certain distributed source cases. Finally, we apply our methods to real MEG data, the N2O response after electric stimulation of the median nerve known to be an extended source.

Algorithms↗

PubMed2005

Efficient electromagnetic source imaging with adaptive standardized LORETA/FOCUSS.

Functional brain imaging and source localization based on the scalp's potential field require a solution to an ill-posed inverse problem with many solutions. This makes it necessary to incorporate a priori knowledge in order to select a particular solution. A computational challenge for some subject-specific head models is that many inverse algorithms require a comprehensive sampling of the candidate source space at the desired resolution. In this study, we present an algorithm that can accurately reconstruct details of localized source activity from a sparse sampling of the candidate source space. Forward computations are minimized through an adaptive procedure that increases source resolution as the spatial extent is reduced. With this algorithm, we were able to compute inverses using only 6% to 11% of the full resolution lead-field, with a localization accuracy that was not significantly different than an exhaustive search through a fully-sampled source space. The technique is, therefore, applicable for use with anatomically-realistic, subject-specific forward models for applications with spatially concentrated source activity.

Action Potentials↗

PubMed2004

Inhomogeneous propagation of cortical spreading depression-detection by electro- and magnetoencephalography in rats.

Spreading depression (SD) propagates in cortical regions that are different in their morphological and functional characteristics. We tested whether the propagation pattern of spreading depression was different between parts of the cortex. In six adult rats, we recorded the ECoG by a 4 x 4 electrode array that covered parts of the frontal, parietal cortex and the cingulate cortex. Simultaneously a 16-channel magnetoencephalogram was recorded to characterize the development and direction of intracortical ion movements accompanying this phenomenon. Spreading depression was initiated by occipital application of 0.3 molar KCl solution. Depolarization was observed, at first, at lateral cortical regions and then at medial cortical regions. Thereafter, the propagation velocity increased in medial cortical regions and was faster than in lateral regions. Negative potential shifts were detected by all electrodes, but the depolarization reached a maximum over lateral and caudal cortical regions. The recorded magnetic fields indicated the same orientation of currents underlying these fields, which was perpendicular to the wave front and points away from the depolarization region. Overall, the data indicated that propagation patterns of spreading depression differed between parts of the cortex and, thus, propagation was inhomogeneous. This propagation was accompanied by strong currents parallel to the cortical surface.

Animals↗