Electric Field Encephalography as a Tool for Functional Brain Research: A Modeling Study

We introduce the notion of Electric Field Encephalography (EFEG) based on measuring electric fields of the brain and demonstrate, using computer modeling, that given the appropriate electric field sensors this technique may have significant advantages over the current EEG technique. Unlike EEG, EFEG can be used to measure brain activity in a contactless and reference-free manner at significant distances from the head surface. Principal component analysis using simulated cortical sources demonstrated that electric field sensors positioned 3 cm away from the scalp and characterized by the same signal-to-noise ratio as EEG sensors provided the same number of uncorrelated signals as scalp EEG. When positioned on the scalp, EFEG sensors provided 2–3 times more uncorrelated signals. This significant increase in the number of uncorrelated signals can be used for more accurate assessment of brain states for non-invasive brain-computer interfaces and neurofeedback applications. It also may lead to major improvements in source localization precision. Source localization simulations for the spherical and Boundary Element Method (BEM) head models demonstrated that the localization errors are reduced two-fold when using electric fields instead of electric potentials. We have identified several techniques that could be adapted for the measurement of the electric field vector required for EFEG and anticipate that this study will stimulate new experimental approaches to utilize this new tool for functional brain research.     

Application of boundary element method for more accurate localization of EEG dipole sources

The proposed modification of boundary element method (BEM) makes it possible to solve direct EEG problem taking into account individual head geometry. This modification decreases computational cost thus enabling practical usage of BEM for localization of EEG dipole sources. The method developed was applied for error estimation of dipole localization using spherical approximation with the aid of BESA software. It was shown that the localization error of BESA for real head geometry could reach 2 cm.     

Polyion-counterion interaction behavior for sodium carboxymethylcellulose in methanol-water mixed solvent media

Precise measurements on the electrical conductivities have been reported for solutions of sodium carboxymethylcellulose in methanol-water mixed solvent media. The conductivity vs. concentration data have been analyzed on the basis of the scaling theory approach for semidilute polyelectrolyte conductivity. The effects of the temperature, the medium, and the polymer concentration on the fractions of uncondensed counterions, the polyion conductivities, the standard state free energies of counterion association, and the coefficients of friction between the polyion and the solvent have also been investigated and the results have been interpreted from the viewpoints of polyion-countreion interactions, effective charge on the polyion, solvation of counterions and the polyionic sites, and counterion dissociation.     

Dipole Source Localization of Mouse Electroencephalogram Using the Fieldtrip Toolbox

The mouse model is an important research tool in neurosciences to examine brain function and diseases with genetic perturbation in different brain regions. However, the limited techniques to map activated brain regions under specific experimental manipulations has been a drawback of the mouse model compared to human functional brain mapping. Here, we present a functional brain mapping method for fast and robust in vivo brain mapping of the mouse brain. The method is based on the acquisition of high density electroencephalography (EEG) with a microarray and EEG source estimation to localize the electrophysiological origins. We adapted the Fieldtrip toolbox for the source estimation, taking advantage of its software openness and flexibility in modeling the EEG volume conduction. Three source estimation techniques were compared: Distribution source modeling with minimum-norm estimation (MNE), scanning with multiple signal classification (MUSIC), and single-dipole fitting. Known sources to evaluate the performance of the localization methods were provided using optogenetic tools. The accuracy was quantified based on the receiver operating characteristic (ROC) analysis. The mean detection accuracy was high, with a false positive rate less than 1.3% and 7% at the sensitivity of 90% plotted with the MNE and MUSIC algorithms, respectively. The mean center-to-center distance was less than 1.2 mm in single dipole fitting algorithm. Mouse microarray EEG source localization using microarray allows a reliable method for functional brain mapping in awake mouse opening an access to cross-species study with human brain.     

Reliability, repeatability and accuracy of the falling head method for hydraulic conductivity measurements under laboratory conditions

The aim of this study was to verify under lab conditions the reliability, repeatability and accuracy of the falling head method (FHM) for hydraulic conductivity measurements. The FHM is a reliable procedure that has slight variations (less than 10%) in repeated measurements and turns out to be a reliable technique to record the hydraulic conductivities typically described for clogged and unclogged subsurface-flow constructed wetlands (from 4 to ca. 360 m/day). The accuracy of the method is acceptable considering difficulties in the measurement of hydraulic conductivity in highly conductive media. Accordingly, results show measurement deviations of 20% when compared with a laboratory constant head method for highly conductive media (higher than 250 m/day), and 80% for media with low hydraulic conductivity (lower than 50 m/day). The main conclusion of the present paper is that of the FHM is a reliable and repeatable technique for hydraulic conductivity measurements and it is accurate enough for on-site clogging assessment in full-scale constructed wetlands.     

Combined EEG/MEG Can Outperform Single Modality EEG or MEG Source Reconstruction in Presurgical Epilepsy Diagnosis

We investigated two important means for improving source reconstruction in presurgical epilepsy diagnosis. The first investigation is about the optimal choice of the number of epileptic spikes in averaging to (1) sufficiently reduce the noise bias for an accurate determination of the center of gravity of the epileptic activity and (2) still get an estimation of the extent of the irritative zone. The second study focuses on the differences in single modality EEG (80-electrodes) or MEG (275-gradiometers) and especially on the benefits of combined EEG/MEG (EMEG) source analysis. Both investigations were validated with simultaneous stereo-EEG (sEEG) (167-contacts) and low-density EEG (ldEEG) (21-electrodes). To account for the different sensitivity profiles of EEG and MEG, we constructed a six-compartment finite element head model with anisotropic white matter conductivity, and calibrated the skull conductivity via somatosensory evoked responses. Our results show that, unlike single modality EEG or MEG, combined EMEG uses the complementary information of both modalities and thereby allows accurate source reconstructions also at early instants in time (epileptic spike onset), i.e., time points with low SNR, which are not yet subject to propagation and thus supposed to be closer to the origin of the epileptic activity. EMEG is furthermore able to reveal the propagation pathway at later time points in agreement with sEEG, while EEG or MEG alone reconstructed only parts of it. Subaveraging provides important and accurate information about both the center of gravity and the extent of the epileptogenic tissue that neither single nor grand-averaged spike localizations can supply.     

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.     

头部组织三维核磁共振电阻抗成像算法的仿真研究

文章给出了一种基于核磁共振技术的三维阻抗成像（电导率分布）重构算法,并将该方法应用于人体头部组织电导率分布重构上。该代数重构方法是利用高分辨率的核磁共振成像系统对成像物体进行三维构建和不同组织的边界区分,根据核磁共振系统中测量得到的磁感应强度Bx和By分量并结合有限元数值计算得到的电流密度分布J组成非线性矩阵,通过迭代求解此非线性矩阵,来解决三维电导率分布的重构问题。在三层球头模型（包括头皮、颅骨和大脑）上分别进行的仿真实验结果表明,该算法具有较强的抗噪声能力和较好的收敛性,重构的头部电导率分布图像具有较高的精确性。     

Distortion of magnetic evoked fields and surface potentials by conductivity differences at boundaries in brain tissue.

We investigated the conditions under which inhomogeneity in electrical conductivity may significantly modify the magnetic evoked field (MEF) due to primary currents (i.e., neuronal currents) in the brain. In the case of an isolated turtle cerebellum immersed in a large bath of physiological saline, our theoretical analysis showed the cerebellar surface to significantly enhance the MEF due to a primary current, by a factor of as much as two, for experimentally determined values of the conductivities of the cerebellar tissue and saline. A further parametric investigation of the conductivity effect revealed that conductivity boundaries may significantly modify the MEF due to neuronal currents located within 1 mm of a conductivity boundary, as would be the case for active neurons near an edema, an anoxic fringe such as might occur during stroke, or a ventricle in the human head. For a stationary neural source, conductivity boundaries may modify the magnitude of its MEF without affecting its temporal waveform. However, this boundary effect was found to be small for a model geometry locally approximating cortical sources in a sulcus or a fissure, where the boundary effects from adjacent sulcal walls tend to cancel each other.     

Effects of cavities on EEG dipole localization and their relations with surface electrode positions

Effects of cavities in the human head on EEG dipole localization have been investigated by computer simulation. The human head is represented by a homogeneous spherical conductor including an eccentric spherical cavity which approximates effects of actual cavities inside the head. The homogeneous sphere model is used for assessing the effects caused by neglecting the cavity in the volume conductor model in the inverse dipole fitting procedure. Four electrode configurations have been examined to investigate their relation to the EEG inverse dipole solution. After examination of 2520 dipoles in the brain, the effects of cavities in the human head are found to be negligible when the dipole is located in the cortex or in the subcortex. When the dipole is located in the brain stem, the EEG inverse dipole solution is strongly affected by the cavity and is sensitive to the electrode configuration on the scalp. The EEG inverse dipole solution in the deep brain is sensitive to inhomogeneity in the lower part of the head when a single positive or negative potential pole is observed by the electrodes on the scalp, and at the same time is sensitive to the extent of the scalp covered by the electrodes. In conclusion, the electrodes should cover as much of the upper scalp as possible for deep source localization.     

Evaluation of centrifugal methods for measuring xylem cavitation in conifers, diffuse- and ring-porous angiosperms

A centrifugal method is used to measure 'vulnerability curves' which show the loss of hydraulic conductivity in xylem by cavitation. Until recently, conductivity was measured between bouts of centrifugation using a gravity-induced head. Now, conductivity can be measured during centrifugation. This 'spin' method is faster than the 'gravity' technique, but correspondence between the two has not been evaluated. The two methods were compared on the same stem segments for two conifer, four diffuse-porous, and four ring-porous species. Only 17 of 60 conductivity measurements differed, with differences in the order of 10%. When different, the spin method gave higher conductivities at the beginning of the curve and lower at the end. Pressure at 50% loss of conductivity, and mean cavitation pressure, were the same in 14 of 20 comparisons. When different, the spin method averaged 0.32 MPa less negative. Ring-porous species showed a precipitous initial drop in conductivity by both techniques. This striking pattern was confirmed by the air-injection method and native embolism measurements. Close correspondence inspires confidence in both methods, each of which has unique advantages. The observation that ring-porous species operate at only a fraction of their potential conductivity at midday demands further study.     

Seizure source localization using a hybrid second order blind identification and extended rival penalized competitive learning algorithm

Localization of seizure sources prior to neurosurgery is crucial. In this paper, a new method is proposed to localize the seizure sources from multi-channel electroencephalogram (EEG) signals. Blind source separation based on second order blind identification (SOBI) is primarily applied to estimate the brain source signals in each window of the EEG signals. A new clustering method based on rival penalized competitive learning (RPCL) is then developed to cluster the rows of the estimated unmixing matrices in all the windows. The algorithm also includes pre and post-processing stages. By multiplying each cluster center to the EEG signals, the brain signal sources are approximated. According to a complexity value measure, the main seizure source signal is separated from the others. This signal is projected back to the electrodes’ space and is subjected to the dipole source localization using a single dipole model. The simulation results verify the accuracy of the system. In addition, correct localization of the seizure source is consistent with the clinical tests derived using the simultaneous intracranial recordings.     

The influence of local tissue conductivity changes on the magnetoencephalogram and the electroencephalogram.

We examined the influence of local tissue conductivity changes in the vicinity of a dipolar source on the neuromagnetic field and the electric scalp potential using a high resolution finite element method model of the human head. We found that the topology of both the electric scalp potential and the neuromagnetic field (and consequently dipole localization) is influenced significantly by conductivity changes only in voxels adjacent to the source. Conductivity changes in these voxels yield a greater change in the amplitude of the magnetic field (and consequently in the dipole strength) than in the amplitude of the electric potential.     

The influence of conductivity changes in boundary element compartments on the forward and inverse problem in electroencephalography and magnetoencephalography.

Source localization based on magnetoencephalographic and electroencephalographic data requires knowledge of the conductivity values of the head. The aim of this paper is to examine the influence of compartment conductivity changes on the neuromagnetic field and the electric scalp potential for the widely used three compartment boundary element models. Both the analysis of measurement data and the simulations with dipoles distributed in the brain produced two significant results. First, we found the electric potentials to be approximately one order of magnitude more sensitive to conductivity changes than the magnetic fields. This was valid for the field and potential topology (and hence dipole localization), and for the amplitude (and hence dipole strength). Second, changes in brain compartment conductivity yield the lowest change in the electric potentials topology (and hence dipole localization), but a very strong change in the amplitude (and hence in the dipole strength). We conclude that for the magnetic fields the influence of compartment conductivity changes is not important in terms of dipole localization and strength estimation. For the electric potentials however, both dipole localization and strength estimation are significantly influenced by the compartment conductivity.     

Monitoring changes in lung air and liquid volumes with electrical impedance tomography

Adler, A., R. Amyot, R. Guardo, J. H. T. Bates, and Y. Berthiaume. Monitoring changes in lung air and liquid volumes withelectrical impedance tomography. J. Appl.Physiol. 83(5): 1762-1767, 1997.Electricalimpedance tomography (EIT) uses electrical measurements at electrodesplaced around the thorax to image changes in the conductivitydistribution within the thorax. This technique is well suited tostudying pulmonary function because the movement of air, blood, andextravascular fluid induces significant conductivity changes within thethorax. We conducted three experimental protocols in a total of 19 dogsto assess the accuracy with which EIT can quantify changes in thevolumes of both gas and fluid in the lungs. In the first protocol, lungvolume increments from 50 to 1,000 ml were applied with a largesyringe. EIT measured these volume changes with an average error of 27 ± 6 ml. In the second protocol, EIT measurements were made at endexpiration and end inspiration during regular ventilation with tidalvolume ranging from 100 to 1,000 ml. The average error in the EITestimates of tidal volume was 90 ± 43 ml. In the third protocol,lung liquid volume was measured by instilling 5% albumin solution intoa lung lobe in increments ranging from 10 to 100 ml. EIT measured thesevolume changes with an average error of 10 ± 10 ml and was alsoable to detect into which lobe the fluid had been instilled. These results indicate that EIT can noninvasively measure changes in thevolumes of both gas and fluid in the lungs with clinically usefulaccuracy.

     

Source localization of induced cortical oscillations during tactile finger stimulation.

We investigated the EEG beta event-related synchronization (ERS) after tactile finger stimulation in three subjects. Prior studies from our group using electrical stimulation and self-paced movement showed a beta rebound within one second after stimulation respectively movement offset. As the tactile-stimulation-data showed a similar ERS behaviour, we extracted the cortical sources for this beta rebound by the linear estimation method in order to see whether the representation areas of different fingers were distinguishable (as is possible with MEG data). Although realistic head models of two subjects were used for the calculations the fingers could not be spatially distinguished. However, regarding the whole spatio-temporal pattern of the ERS for different fingers clear differences can be observed.     

An investigation of the phase locking index for measuring of interdependency of cortical source signals recorded in the EEG

The phase locking index (PLI) was introduced to quantify in a statistical sense the phase synchronization of two signals. It has been commonly used to process biosignals. In this article, we investigate the PLI for measuring the interdependency of cortical source signals (CSSs) recorded in the Electroencephalogram (EEG). To this end, we consider simple analytical models for the mapping of simulated CSSs into the EEG. For these models, the PLI is investigated analytically and through numerical simulations. An evaluation is made of the sensitivity of the PLI to the amount of crosstalk between the sources through biological tissues of the head. It is found that the PLI is a useful interdependency measure for CSSs, especially when the amount of crosstalk is small. Another common interdependency measure is the coherence. A direct comparison of both measures has not been made in the literature so far. We assess the performance of the PLI and coherence for estimation and detection purposes based on, respectively, a normalized variance and a novel statistical measure termed contrast. Based on these performance measures, it is found that the PLI is similar or better than the CM in most cases. This result is also confirmed through analysis of EEGs recorded from epileptic patients.

A Computer Model of Engineered Cardiac Monolayers

Engineered monolayers created using microabrasion and micropatterning methods have provided a simplified in vitro system to study the effects of anisotropy and fiber direction on electrical propagation. Interpreting the behavior in these culture systems has often been performed using classical computer models with continuous properties. However, such models do not account for the effects of random cell shapes, cell orientations, and cleft spaces inherent in these monolayers on the resulting wavefront conduction. This work presents a novel methodology for modeling a monolayer of cardiac tissue in which the factors governing cell shape, cell-to-cell coupling, and degree of cleft space are not constant but rather are treated as spatially random with assigned distributions. This modeling approach makes it possible to simulate wavefront propagation in a manner analogous to performing experiments on engineered monolayer tissues. Simulated results are compared to previously published measured data from monolayers used to investigate the role of cellular architecture on conduction velocities and anisotropy ratios. We also present an estimate for obtaining the electrical properties from these networks and demonstrate how variations in the discrete cellular architecture affect the macroscopic conductivities. The simulations support the common assumption that under normal ranges of coupling strength, tissues with relatively uniform distributions of cell shapes and connectivity can be represented using continuous models with conductivities derived from random discrete cellular architecture using either global or local estimates. The results also reveal that in the presence of abrupt changes in cell orientation, local estimates of tissue properties predict smoother changes in conductivity that may not adequately predict the discrete nature of propagation at the transition sites.     

Tetrapolar measurement of electrical conductivity and thickness of articular cartilage

A tetrapolar method to measure electrical conductivity of cartilage and bone, and to estimate the thickness of articular cartilage attached to bone, was developed. We determined the electrical conductivity of humeral head bovine articular cartilage and subchondral bone from a 1- to 2-year-old steer to be 1.14+/-0.11 S/m (mean+/-sd, n =11) and 0.306+/-0.034 S/m, (mean+/-sd, n =3), respectively. For a 4-year-old cow, articular cartilage and subchondral bone electrical conductivity were 0.88+/-0.08 S/m (mean+/-sd, n =9) and 0.179+/-0.046 S/m (mean+/-sd, n =3), respectively. Measurements on slices of cartilage taken from different distances from the articular surface of the steer did not reveal significant depth-dependence of electrical conductivity. We were able to estimate the thickness of articular cartilage with reasonable precision (<20% error) by injecting current from multiple electrode pairs with different inter-electrode distances. Requirements for the precision of this method to measure cartilage thickness include the presence of a distinct layer of calcified cartilage or bone with a much lower electrical conductivity than that of uncalcified articular cartilage, and the use of inter-electrode distances of the current injecting electrodes that are on the order of the cartilage thickness. These or similar methods present an attractive approach to the non-destructive determination of cartilage thickness, a parameter that is required in order to estimate functional properties of cartilage attached to bone, and evaluate the need for therapeutic interventions in arthritis.