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Introduction: Electrical activity of the myocardium is recorded with the 12-lead ECG. ECG simulations can improve our understanding of the relation between abnormal ventricular activation in diseased myocardium and body surface potentials (BSP). However, in equivalent dipole layer (EDL)-based ECG simulations, the presence of diseased myocardium breaks the equivalence of the dipole layer. To simulate diseased myocardium, patches with altered electrophysiological characteristics were incorporated within the model. The relation between diseased myocardium and corresponding BSP was investigated in a simulation study. Methods: Activation sequences in normal and diseased myocardium were simulated and corresponding 64-lead BSP were computed in four models with distinct patch locations. QRS-complexes were compared using correlation coefficient (CC). The effect of different types of patch activation was assessed. Of one patient, simulated electrograms were compared to electrograms recorded during invasive electro-anatomical mapping. Results: Hundred-fifty-three abnormal activation sequences were simulated. Median QRS-CC of delayed versus dyssynchronous were significantly different (1.00 vs. 0.97, p < 0.001). Depending on the location of the patch, BSP leads were affected differently. Within diseased regions, fragmentation, low bipolar voltages and late potentials were observed in both recorded and simulated electrograms. Discussion: A novel method to simulate cardiomyopathy in EDL-based ECG simulations was established and evaluated. The new patch-based approach created a realistic relation between ECG waveforms and underlying activation sequences. Findings in the simulated cases were in agreement with clinical observations. With this method, our understanding of disease progression in cardiomyopathies may be further improved and used in advanced inverse ECG procedures., Competing Interests: Peter M van Dam is owner of ECG Excellence BV. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Boonstra, Oostendorp, Roudijk, Kloosterman, Asselbergs, Loh and Van Dam.)

Inverse electrocardiography (iECG) estimates epi- and endocardial electrical activity from body surface potentials maps (BSPM). In individuals at risk for cardiomyopathy, non-invasive estimation of normal ventricular activation may provide valuable information to aid risk stratification to prevent sudden cardiac death. However, multiple simultaneous activation wavefronts initiated by the His-Purkinje system, severely complicate iECG. To improve the estimation of normal ventricular activation, the iECG method should accurately mimic the effect of the His-Purkinje system, which is not taken into account in the previously published multi-focal iECG. Therefore, we introduce the novel multi-wave iECG method and report on its performance. Multi-wave iECG and multi-focal iECG were tested in four patients undergoing invasive electro-anatomical mapping during normal ventricular activation. In each subject, 67-electrode BSPM were recorded and used as input for both iECG methods. The iECG and invasive local activation timing (LAT) maps were compared. Median epicardial inter-map correlation coefficient (CC) between invasive LAT maps and estimated multi-wave iECG versus multi-focal iECG was 0.61 versus 0.31. Endocardial inter-map CC was 0.54 respectively 0.22. Modeling the His-Purkinje system resulted in a physiologically realistic and robust non-invasive estimation of normal ventricular activation, which might enable the early detection of cardiac disease during normal sinus rhythm., (© 2022. The Author(s).)

Transcranial direct current stimulation (tDCS) is a promising tool to improve and speed up motor rehabilitation after stroke, but inconsistent clinical effects refrain tDCS from clinical implementation. Therefore, this study aimed to assess the need for individualized tDCS configurations in stroke, considering interindividual variability in brain anatomy and motor function representation. We simulated tDCS in individualized MRI-based finite element head models of 21 chronic stroke subjects and 10 healthy age-matched controls. An anatomy-based stimulation target, i.e. the motor hand knob, was identified with MRI, whereas a motor function-based stimulation target was identified with EEG. For each subject, we simulated conventional anodal tDCS electrode configurations and optimized electrode configurations to maximize stimulation strength within the anatomical and functional target. The normal component of the electric field was extracted and compared between subjects with stroke and healthy, age-matched controls, for both targets, during conventional and optimized tDCS. Electrical field strength was significantly lower, more variable and more frequently in opposite polarity for subjects with stroke compared to healthy age-matched subjects, both for the anatomical and functional target with conventional, i.e. non-individualized, electrode configurations. Optimized, i.e. individualized, electrode configurations increased the electrical field strength in the anatomical and functional target for subjects with stroke but did not reach the same levels as in healthy subjects. Considering individual brain structure and motor function is crucial for applying tDCS in subjects with stroke. Lack of individualized tDCS configurations in subjects with stroke results in lower electric fields in stimulation targets, which may partially explain the inconsistent clinical effects of tDCS in stroke trials., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background: The detection and localization of electrophysiological substrates currently involve invasive cardiac mapping. Electrocardiographic imaging (ECGI) using the equivalent dipole layer (EDL) method allows the noninvasive estimation of endocardial and epicardial activation and repolarization times (AT and RT), but the RT validation is limited to in silico studies. We aimed to assess the temporal and spatial accuracy of the EDL method in reconstructing the RTs from the surface ECG under physiological circumstances and situations with artificially induced increased repolarization heterogeneity. Methods: In four Langendorff-perfused pig hearts, we simultaneously recorded unipolar electrograms from plunge needles and pseudo-ECGs from a volume-conducting container equipped with 61 electrodes. The RTs were computed from the ECGs during atrial and ventricular pacing and compared with those measured from the local unipolar electrograms. Regional RT prolongation (cooling) or shortening (pinacidil) was achieved by selective perfusion of the left anterior descending artery (LAD) region. Results: The differences between the computed and measured RTs were 19.0 ± 17.8 and 18.6 ± 13.7 ms for atrial and ventricular paced beats, respectively. The region of artificially delayed or shortened repolarization was correctly identified, with minimum/maximum RT roughly in the center of the region in three hearts. In one heart, the reconstructed region was shifted by ~2.5 cm. The total absolute difference between the measured and calculated RTs for all analyzed patterns in selectively perfused hearts ( n = 5) was 39.6 ± 27.1 ms. Conclusion: The noninvasive ECG repolarization imaging using the EDL method of atrial and ventricular paced beats allows adequate quantitative reconstruction of regions of altered repolarization., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 van der Waal, Meijborg, Belterman, Streekstra, Oostendorp and Coronel.)

The inconsistent response to transcranial electric stimulation in the stroke population is attributed to, among other factors, unknown effects of stroke lesion conductivity on stimulation strength at the targeted brain areas. Volume conduction models are promising tools to determine optimal stimulation settings. However, stroke lesion conductivity is often not considered in these models as a source of inter-subject variability. The goal of this study is to propose a method that combines MRI, EEG, and transcranial stimulation to estimate the conductivity of cortical stroke lesions experimentally. In this simulation study, lesion conductivity was estimated from scalp potentials during transcranial electric stimulation in 12 chronic stroke patients. To do so, first, we determined the stimulation configuration where scalp potentials are maximally affected by the lesion. Then, we calculated scalp potentials in a model with a fixed lesion conductivity and a model with a randomly assigned conductivity. To estimate the lesion conductivity, we minimized the error between the two models by varying the conductivity in the second model. Finally, to reflect realistic experimental conditions, we test the effect rotation of measurement electrode orientation and the effect of the number of electrodes used. We found that the algorithm converged to the correct lesion conductivity value when noise on the electrode positions was absent for all lesions. Conductivity estimation error was below 5% with realistic electrode coregistration errors of 0.1° for lesions larger than 50 ml. Higher lesion conductivities and lesion volumes were associated with smaller estimation errors. In conclusion, this method can experimentally estimate stroke lesion conductivity, improving the accuracy of volume conductor models of stroke patients and potentially leading to more effective transcranial electric stimulation configurations for this population., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 van der Cruijsen, Piastra, Selles and Oostendorp.)

This study presents a novel non-invasive equivalent dipole layer (EDL) based inverse electrocardiography ( i ECG) technique which estimates both endocardial and epicardial ventricular activation sequences. We aimed to quantitatively compare our i ECG approach with invasive electro-anatomical mapping (EAM) during sinus rhythm with the objective of enabling functional substrate imaging and sudden cardiac death risk stratification in patients with cardiomyopathy. Thirteen patients (77% males, 48 ± 20 years old) referred for endocardial and epicardial EAM underwent 67-electrode body surface potential mapping and CT imaging. The EDL-based i ECG approach was improved by mimicking the effects of the His-Purkinje system on ventricular activation. EAM local activation timing (LAT) maps were compared with i ECG-LAT maps using absolute differences and Pearson's correlation coefficient, reported as mean ± standard deviation [95% confidence interval]. The correlation coefficient between i ECG-LAT maps and EAM was 0.54 ± 0.19 [0.49-0.59] for epicardial activation, 0.50 ± 0.27 [0.41-0.58] for right ventricular endocardial activation and 0.44 ± 0.29 [0.32-0.56] for left ventricular endocardial activation. The absolute difference in timing between i ECG maps and EAM was 17.4 ± 7.2 ms for epicardial maps, 19.5 ± 7.7 ms for right ventricular endocardial maps, 27.9 ± 8.7 ms for left ventricular endocardial maps. The absolute distance between right ventricular endocardial breakthrough sites was 30 ± 16 mm and 31 ± 17 mm for the left ventricle. The absolute distance for latest epicardial activation was median 12.8 [IQR: 2.9-29.3] mm. This first in-human quantitative comparison of i ECG and invasive LAT-maps on both the endocardial and epicardial surface during sinus rhythm showed improved agreement, although with considerable absolute difference and moderate correlation coefficient. Non-invasive i ECG requires further refinements to facilitate clinical implementation and risk stratification., Competing Interests: PD is owner of ECG Excellence BV. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Roudijk, Boonstra, Brummel, Kassenberg, Blom, Oostendorp, te Riele, van der Heijden, Asselbergs, van Dam and Loh.)

We describe and evaluate our practice-based learning approach for research in undergraduate students studying Biomedical Sciences at Radboud University Nijmegen, the Netherlands. First-year students who started their study between 2015 and 2018 actively participated in data collection and measurements, including anthropometry, electrocardiogram findings, genetic variants, and lifestyle habits. All data were entered into one anonymous database , which was used by students to analyze their research questions. In 2019, 44 of the 87 students (50%) valued active measurements better than questionnaires. Most students (strongly) agreed that they have learned about data collection and were inspired to learn more about biomedical research., (© The Author(s) 2021.)

Objective: Implantable electrodes, such as electrocorticography (ECoG) grids, are used to record brain activity in applications like brain computer interfaces. To improve the spatial sensitivity of ECoG grid recordings, electrode properties need to be better understood. Therefore, the goal of this study is to analyze the importance of including electrodes explicitly in volume conduction calculations., Approach: We investigated the influence of ECoG electrode properties on potentials in three geometries with three different electrode models. We performed our simulations with FEMfuns, a volume conduction modeling software toolbox based on the finite element method., Main Results: The presence of the electrode alters the potential distribution by an amount that depends on its surface impedance, its distance from the source and the strength of the source. Our modeling results show that when ECoG electrodes are near the sources the potentials in the underlying tissue are more uniform than without electrodes. We show that the recorded potential can change up to a factor of 3, if no extended electrode model is used. In conclusion, when the distance between an electrode and the source is equal to or smaller than the size of the electrode, electrode effects cannot be disregarded. Furthermore, the potential distribution of the tissue under the electrode is affected up to depths equal to the radius of the electrode., Significance: This paper shows the importance of explicitly including electrode properties in volume conduction models for accurately interpreting ECoG measurements.

Applications such as brain computer interfaces require recordings of relevant neuronal population activity with high precision, for example, with electrocorticography (ECoG) grids. In order to achieve this, both the placement of the electrode grid on the cortex and the electrode properties, such as the electrode size and material, need to be optimized. For this purpose, it is essential to have a reliable tool that is able to simulate the extracellular potential, i.e., to solve the so-called ECoG forward problem, and to incorporate the properties of the electrodes explicitly in the model. In this study, this need is addressed by introducing the first open-source pipeline, FEMfuns (finite element method for useful neuroscience simulations), that allows neuroscientists to solve the forward problem in a variety of different geometrical domains, including different types of source models and electrode properties, such as resistive and capacitive materials. FEMfuns is based on the finite element method (FEM) implemented in FEniCS and includes the geometry tessellation, several electrode-electrolyte implementations and adaptive refinement options. The Python code of the pipeline is available under the GNU General Public License version 3 at https://github.com/meronvermaas/FEMfuns . We tested our pipeline with several geometries and source configurations such as a dipolar source in a multi-layer sphere model and a five-compartment realistically-shaped head model. Furthermore, we describe the main scripts in the pipeline, illustrating its flexible and versatile use. Provided with a sufficiently fine tessellation, the numerical solution of the forward problem approximates the analytical solution. Furthermore, we show dispersive material and interface effects in line with previous literature. Our results indicate substantial capacitive and dispersive effects due to the electrode-electrolyte interface when using stimulating electrodes. The results demonstrate that the pipeline presented in this paper is an accurate and flexible tool to simulate signals generated on electrode grids by the spatiotemporal electrical activity patterns produced by sources and thereby allows the user to optimize grids for brain computer interfaces including exploration of alternative electrode materials/properties.

Electrocardiographic Imaging (ECGI) requires robust ECG forward simulations to accurately calculate cardiac activity. However, many questions remain regarding ECG forward simulations, for instance: there are not common guidelines for the required cardiac source sampling. In this study we test equivalent double layer (EDL) forward simulations with differing cardiac source resolutions and different spatial interpolation techniques. The goal is to reduce error caused by undersampling of cardiac sources and provide guidelines to reduce said source undersampling in ECG forward simulations. Using a simulated dataset sampled at 5 spatial resolutions, we computed body surface potentials using an EDL forward simulation pipeline. We tested two spatial interpolation methods to reduce error due to undersampling triangle weighting and triangle splitting. This forward modeling pipeline showed high frequency artifacts in the predicted ECG time signals when the cardiac source resolution was too low. These low resolutions could also cause shifts in extrema location on the body surface maps. However, these errors in predicted potentials can be mitigated by using a spatial interpolation method. Using spatial interpolation can reduce the number of nodes required for accurate body surface potentials from 9,218 to 2,306. Spatial interpolation in this forward model could also help improve accuracy and reduce computational cost in subsequent ECGI applications.

The blood-brain barrier (BBB) limits the access of drugs to the brain. Intensive research is being conducted on the development of nanoparticulate drug carriers that mediate transfer across the BBB. A question that has been neglected so far is the potential accumulation of the carrier in the brain upon long-term exposure. Here, we address this question by implementing a kinetic model to relate drug loading, required concentration of drug in the brain, and drug clearance to the degradation half-life of the carrier. As a test case with clinical relevance we chose poly-lactic-co-glycolic-acid (PLGA) as a carrier material and a chemotherapeutic for which the required parameters could be recovered from the literature. For methotrexate with a drug load of 8.5 %, a required concentration of free drug of 1 μm, a release from PLGA of 6 hours, a drug clearance from the brain of 3 hours and a half-life of polymer degradation of 28 days, a steady-state accumulation of 1.3 g polymer would be reached in the brain (1.5 L) after seven months. While this number is surprisingly small, further physiological research is warranted to assess to which degree this will be in a tolerable range., (© 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Promising results have been reported in noninvasive estimation of cardiac activation times (AT) using the equivalent dipole layer (EDL) source model in combination with the boundary element method (BEM). However, the assumption of equal anisotropy ratios in the heart that underlies the EDL model does not reflect reality. In the present study, we quantify the errors of the nonlinear AT imaging based on the EDL approximation. Nine different excitation patterns (sinus rhythm and eight ectopic beats) were simulated with the monodomain model. Based on the bidomain theory, the body surface potential maps (BSPMs) were calculated for a realistic finite element volume conductor with an anisotropic heart model. For the forward calculations, three cases of bidomain conductivity tensors in the heart were considered: isotropic, equal, and unequal anisotropy ratios in the intra- and extracellular spaces. In all inverse reconstructions, the EDL model with BEM was employed: AT were estimated by solving the nonlinear optimization problem with the initial guess provided by the fastest route algorithm. Expectedly, the case of unequal anisotropy ratios resulted in larger localization errors for almost all considered activation patterns. For the sinus rhythm, all sites of early activation were correctly estimated with an optimal regularization parameter being used. For the ectopic beats, all but one foci were correctly classified to have either endo- or epicardial origin with an average localization error of 20.4 mm for unequal anisotropy ratio. The obtained results confirm validation studies and suggest that cardiac anisotropy might be neglected in clinical applications of the considered EDL-based inverse procedure.

Background: Noninvasive imaging of cardiac activation before ablation of the arrhythmogenic substrate can reduce electrophysiological procedure duration and help choosing between an endocardial or epicardial approach. A noninvasive imaging technique was evaluated that estimates both endocardial and epicardial activation from body surface potential maps. We performed a study in isolated and in situ pig hearts, estimating activation from body surface potential maps during sinus rhythm and localizing endocardial and epicardial stimulation sites., Methods and Results: From 3 Langendorff-perfused pig hearts, 180 intramural unipolar electrograms were recorded during sinus rhythm and ectopic activation, together with pseudo-body surface potential map ECGs in 2 of them. From 4 other anesthetized pigs, 64-lead body surface potential maps were recorded during sinus rhythm and ventricular stimulation from 27 endocardial and epicardial sites. The ventricular activation pattern was computed from the recorded QRS complexes. For both Langendorff-perfused hearts, the calculated epicardial and endocardial activation patterns showed good qualitative correspondence to the patterns obtained with needle electrodes. Absolute timing difference for sinus rhythm was 10±5 and 11±8 ms respectively, and for ectopic activation 6±5 and 7±6 ms, respectively. Calculated activation for the in situ hearts in sinus rhythm was similar to patterns recorded in Langendorff-perfused hearts. During stimulation, the distance between the stimulation site and calculated site of earliest activation was 18 (15-27) mm, and 23 of 27 stimulation sites were correctly mapped to either endocardium or epicardium., Conclusions: Noninvasive activation imaging is able to determine earliest ventricular activation and discriminate endocardial from epicardial origin of activation with clinically relevant accuracy., (© 2016 American Heart Association, Inc.)

Background: Characteristics of the ventricular fibrillation (VF) waveform reflect arrest duration and have been incorporated in studies on algorithms to guide resuscitative interventions. Findings in animals indicate that VF characteristics are also affected by the presence of a previous myocardial infarction (MI). As studies in humans are scarce, we assessed the impact of a previous MI on VF characteristics in ICD-patients., Methods: Prospective cohort of ICD-patients (n=190) with defibrillation testing at the Radboudumc (2010-2013). VF characteristics of the 12-lead surface ECG were compared between three groups: patients without a history of MI (n=88), with a previous anterior (n=47) and a previous inferior MI (n=55)., Results: As compared to each of the other groups, the mean amplitude and amplitude spectrum area were lower, for an anterior MI in lead V3 and for an inferior MI in leads II and aVF. Across the three groups, the bandwidth was broader in the leads corresponding with the infarct localisation. In contrast, the dominant and median frequencies only differed between previous anterior MI and no history of MI, being lower in the former., Conclusions: The VF waveform is affected by the presence of a previous MI. Amplitude-related measures were lower and VF was less organised in the ECG-lead(s) adjacent to the area of infarction. Although VF characteristics of the surface ECG have so far primarily been considered a proxy for arrest duration and metabolic state, our findings question this paradigm and may provide additional insights into the future potential of VF-guided resuscitative interventions., (Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.)

Background: The effectiveness of transcranial magnetic stimulation (TMS) depends highly on the coil orientation relative to the subject's head. This implies that the direction of the induced electric field has a large effect on the efficiency of TMS. To improve future protocols, knowledge about the relationship between the coil orientation and the direction of the induced electric field on the one hand, and the head and brain anatomy on the other hand, seems crucial. Therefore, the induced electric field in the cortex as a function of the coil orientation has been examined in this study., Methods: The effect of changing the coil orientation on the induced electric field was evaluated for fourteen cortical targets. We used a finite element model to calculate the induced electric fields for thirty-six coil orientations (10 degrees resolution) per target location. The effects on the electric field due to coil rotation, in combination with target site anatomy, have been quantified., Results: The results confirm that the electric field perpendicular to the anterior sulcal wall of the central sulcus is highly susceptible to coil orientation changes and has to be maximized for an optimal stimulation effect of the motor cortex. In order to obtain maximum stimulation effect in areas other than the motor cortex, the electric field perpendicular to the cortical surface in those areas has to be maximized as well. Small orientation changes (10 degrees) do not alter the induced electric field drastically., Conclusions: The results suggest that for all cortical targets, maximizing the strength of the electric field perpendicular to the targeted cortical surface area (and inward directed) optimizes the effect of TMS. Orienting the TMS coil based on anatomical information (anatomical magnetic resonance imaging data) about the targeted brain area can improve future results. The standard coil orientations, used in cognitive and clinical neuroscience, induce (near) optimal electric fields in the subject-specific head model in most cases.

Background: Ventricular fibrillation (VF) waveform characteristics are associated with cardiac arrest duration and defibrillation success. Recent animal studies found that VF characteristics and shock success also depend on the presence of myocardial infarction (MI). In patients, VF induction after implantable cardioverter defibrillator (ICD) implantation offers a unique setting to study early VF characteristics: we studied the relation with cardiac disease--either presence or absence of a previous MI--and with shock success., Methods: Retrospective cohort study of ICD-patients who underwent defibrillation testing, 117 (63%) with and 69 (37%) without a previous MI. Intracardiac recordings of induced VF were analysed using Fourier analysis., Results: In previous MI-patients, the fundamental frequency and organisation index of the VF signal were significantly lower as compared with patients without a previous MI: 4.9 Hz ± 0.6 vs. 5.2 Hz ± 0.6 (p = 0.005) and 56% ± 10 vs. 60% ± 9 (p = 0.001), respectively. The median frequency was not different (p = 0.25). We found no association between VF characteristics and ICD shock success., Conclusions: In analogy with observations in animals, we found that a history of a previous MI was associated with slower and less organised VF. In our cohort of ICD-patients, early VF waveform characteristics were not associated with shock outcomes. Further study is warranted to determine to what extent VF characteristics are influenced by the underlying aetiology on the one hand, and time delay on the other. These findings could improve insight into the potential value of VF analysis to guide shock delivery., (Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.)

Many human cortical regions are targeted with transcranial magnetic stimulation (TMS). The stimulus intensity used for a certain region is generally based on the motor threshold stimulation intensity determined over the motor cortex (M1). However, it is well known that differences exist in coil-target distance and target site anatomy between cortical regions. These differences may well make the stimulation intensity derived from M1 sub-optimal for other regions. Our goal was to determine in what way the induced electric fields differ between cortical target regions. We used finite element method modeling to calculate the induced electric field for multiple target sites in a realistic head model. The effects on the electric field due to coil-target distance and target site anatomy have been quantified. The results show that a correction based on the distance alone does not correctly adjust the induced electric field for regions other than M1. In addition, a correction based solely on the TMS-induced electric field (primary field) does not suffice. A precise adjustment should include coil-target distance, the secondary field caused by charge accumulation at conductivity discontinuities and the direction of the field relative to the local cerebrospinal fluid-grey matter boundary.

Transcranial direct current stimulation (tDCS) is a noninvasive brain stimulation technique able to induce long-lasting changes in cortical excitability that can benefit cognitive functioning and clinical treatment. In order to both better understand the mechanisms behind tDCS and possibly improve the technique, finite element models are used to simulate tDCS of the human brain. With the detailed anisotropic head model presented in this study, we provide accurate predictions of tDCS in the human brain for six of the practically most-used setups in clinical and cognitive research, targeting the primary motor cortex, dorsolateral prefrontal cortex, inferior frontal gyrus, occipital cortex, and cerebellum. We present the resulting electric field strengths in the complete brain and introduce new methods to evaluate the effectivity in the target area specifically, where we have analyzed both the strength and direction of the field. For all cerebral targets studied, the currently accepted configurations produced sub-optimal field strengths. The configuration for cerebellum stimulation produced relatively high field strengths in its target area, but it needs higher input currents than cerebral stimulation does. This study suggests that improvements in the effects of transcranial direct current stimulation are achievable.

Objective: We investigate volume conduction effects in transcranial direct current stimulation (tDCS) and present a guideline for efficient and yet accurate volume conductor modeling in tDCS using our newly-developed finite element (FE) approach., Approach: We developed a new, accurate and fast isoparametric FE approach for high-resolution geometry-adapted hexahedral meshes and tissue anisotropy. To attain a deeper insight into tDCS, we performed computer simulations, starting with a homogenized three-compartment head model and extending this step by step to a six-compartment anisotropic model., Main Results: We are able to demonstrate important tDCS effects. First, we find channeling effects of the skin, the skull spongiosa and the cerebrospinal fluid compartments. Second, current vectors tend to be oriented towards the closest higher conducting region. Third, anisotropic WM conductivity causes current flow in directions more parallel to the WM fiber tracts. Fourth, the highest cortical current magnitudes are not only found close to the stimulation sites. Fifth, the median brain current density decreases with increasing distance from the electrodes., Significance: Our results allow us to formulate a guideline for volume conductor modeling in tDCS. We recommend to accurately model the major tissues between the stimulating electrodes and the target areas, while for efficient yet accurate modeling, an exact representation of other tissues is less important. Because for the low-frequency regime in electrophysiology the quasi-static approach is justified, our results should also be valid for at least low-frequency (e.g., below 100 Hz) transcranial alternating current stimulation.

Volume conduction models can help in acquiring knowledge about the distribution of the electric field induced by transcranial magnetic stimulation. One aspect of a detailed model is an accurate description of the cortical surface geometry. Since its estimation is difficult, it is important to know how accurate the geometry has to be represented. Previous studies only looked at the differences caused by neglecting the complete boundary between cerebrospinal fluid (CSF) and grey matter (Thielscher et al 2011 NeuroImage 54 234-43, Bijsterbosch et al 2012 Med. Biol. Eng. Comput. 50 671-81), or by resizing the whole brain (Wagner et al 2008 Exp. Brain Res. 186 539-50). However, due to the high conductive properties of the CSF, it can be expected that alterations in sulcus width can already have a significant effect on the distribution of the electric field. To answer this question, the sulcus width of a highly realistic head model, based on T1-, T2- and diffusion-weighted magnetic resonance images, was altered systematically. This study shows that alterations in the sulcus width do not cause large differences in the majority of the electric field values. However, considerable overestimation of sulcus width produces an overestimation of the calculated field strength, also at locations distant from the target location.

In modeling the effect of transcranial direct current stimulation, the representation of the skull is an important factor. In a spherical model, we compared a realistic skull modeling approach, in which the skull consisted of three isotropic layers, to anisotropic and isotropic single-layer approximations. We simulated direct current stimulation for a range of conductivity values and investigated differences in the resulting current densities. Our results demonstrate that both approximation methods perform well, provided that the optimal conductivity values are used. We found that for both the anisotropic and the isotropic approximations the optimal conductivity values are largely dictated by the equivalent radial conductivity of the three-layered skull.

Determining electrical activation of the heart in a noninvasive way is one of the challenges in cardiac electrophysiology. The ECG provides some, but limited information about the electrical status of the heart. This article describes a method to determine both endocardial and epicardial activation of the heart of an individual patient from 64 electrograms recorded from the body surface. Information obtained in this way might be helpful for the treatment of arrhythmias, to assess the effect of drugs on conduction in the heart and to assess electrical stability of the heart.

Brain activity can be measured with several non-invasive neuroimaging modalities, but each modality has inherent limitations with respect to resolution, contrast and interpretability. It is hoped that multimodal integration will address these limitations by using the complementary features of already available data. However, purely statistical integration can prove problematic owing to the disparate signal sources. As an alternative, we propose here an advanced neural population model implemented on an anatomically sound cortical mesh with freely adjustable connectivity, which features proper signal expression through a realistic head model for the electroencephalogram (EEG), as well as a haemodynamic model for functional magnetic resonance imaging based on blood oxygen level dependent contrast (fMRI BOLD). It hence allows simultaneous and realistic predictions of EEG and fMRI BOLD from the same underlying model of neural activity. As proof of principle, we investigate here the influence on simulated brain activity of strengthening visual connectivity. In the future we plan to fit multimodal data with this neural population model. This promises novel, model-based insights into the brain's activity in sleep, rest and task conditions.

This contribution demonstrates some applications of the most recent release of ECGSIM, an interactive simulation program that enables the user to study the relationship between the electric current sources of the heart and the resulting electrocardiographic signals on the body surface as well as those on the surface of the heart. It aims to serve as an educational tool as well as a research tool. The examples are drawn from the topics discussed by the participants of the Magnetic Anatomic and eLectrical Technology meeting in Maastricht, the Netherlands (February 2011), reports of which are to be found in the current issue of the Journal of Electrocardiology. These examples include simulation of the atrial electrocardiogram, improved accessibility of endocardial source locations, and an explanation of ST elevations accompanying true TQ depressions., (Copyright © 2011 Elsevier Inc. All rights reserved.)

Progress in functional neuroimaging of the brain increasingly relies on the integration of data from complementary imaging modalities in order to improve spatiotemporal resolution and interpretability. However, the usefulness of merely statistical combinations is limited, since neural signal sources differ between modalities and are related non-trivially. We demonstrate here that a mean field model of brain activity can simultaneously predict EEG and fMRI BOLD with proper signal generation and expression. Simulations are shown using a realistic head model based on structural MRI, which includes both dense short-range background connectivity and long-range specific connectivity between brain regions. The distribution of modeled neural masses is comparable to the spatial resolution of fMRI BOLD, and the temporal resolution of the modeled dynamics, importantly including activity conduction, matches the fastest known EEG phenomena. The creation of a cortical mean field model with anatomically sound geometry, extensive connectivity, and proper signal expression is an important first step towards the model-based integration of multimodal neuroimages.

The sequences of activation and recovery of the heart have physiological and clinical relevance. We report on progress made over the last years in the method that images these timings based on an equivalent double layer on the myocardial surface serving as the equivalent source of cardiac activity, with local transmembrane potentials (TMP) acting as their strength. The TMP wave forms were described analytically by timing parameters, found by minimizing the difference between observed body surface potentials and those based on the source description. The parameter estimation procedure involved is non-linear, and consequently requires the specification of initial estimates of its solution. Those of the timing of depolarization were based on the fastest route algorithm, taking into account properties of anisotropic propagation inside the myocardium. Those of recovery were based on electrotonic effects. Body surface potentials and individual geometry were recorded on: a healthy subject, a WPW patient and a Brugada patient during an Ajmaline provocation test. In all three cases, the inversely estimated timing agreed entirely with available physiological knowledge. The improvements to the inverse procedure made are attributed to our use of initial estimates based on the general electrophysiology of propagation. The quality of the results and the required computation time permit the application of this inverse procedure in a clinical setting.

Radiofrequency catheter ablation (RCA) procedures for treating ventricular arrhythmias have evolved significantly over the past several years; however, the use of RCA has been limited due to the difficulty in identifying the appropriate site for ablation. In this study, we investigate the accuracy of a computer algorithm to guide the tip of an ablation catheter to the exit site of the scar tissue or the site of abnormal automaticity (the "target site"). This algorithm involves modeling the body surface potentials corresponding to the wavefront at the target site for ablation and current pulses generated from a pair of electrodes at the tip of the ablation catheter with a single equivalent moving dipole (SEMD) in an infinite homogeneous volume conductor. Despite the fact that the use of the homogeneous volume conductor introduces systematic error in the estimated compared to the true dipole location, we find that the systematic error had minor influence in the ability of the algorithm to accurately guide the tip of the ablation catheter to the ablation site and the overall error (1.9 +/- 1.1 mm) in the left ventricle is adequate for RCA procedures. These results were verified, in saline tank studies in which the distance between the dipole due to the catheter tip and the dipole due to the target site was found to be 2.66 +/- 0.52 mm. In conclusion, our algorithm to estimate the SEMD parameters from body surface potentials can potentially be a useful method to rapidly and accurately guide the catheter tip to the arrhythmic site during an RCA procedure.

A method is described to determine the effect on the ECG of a reduced propagation velocity within an ischemic zone. The method was designed to change the activation sequence throughout the ventricles interactively, i.e. with a response time in the order of a second. The timing of ventricular ischemic activation was computed by using the fastest route algorithm, based on locally reduced values of the propagation velocities derived from a standard, normal activation sequence. The effect of these local reductions of the velocities on the total activation sequence, as well as the changes in the electrocardiogram that these produce, are presented.

A method to estimate the potential and current density distribution during transcranial DC stimulation (tDCS) is introduced. The volume conductor model consists of a realistic head model (concerning shape as well as conductivity), obtained from TI-, PD- and DT-MR images. The model includes five compartments with different conductivities. For the skull and the white matter compartments, the conductivities are anisotropic. Using this model, the potentials inside the head that are generated by tDCS electrodes positioned on the scalp were computed by using the Finite Element Method. The results show that this is a promising method for the study of the effects of tDCS.

We have previously proposed an inverse algorithm for fitting potentials due to an arbitrary bio-electrical source to a single equivalent moving dipole (SEMD) model. The algorithm achieves fast identification of the SEMD parameters by employing a SEMD model embedded in an infinite homogeneous volume conductor. However, this may lead to systematic error in the identification of the SEMD parameters. In this paper, we investigate the accuracy of the algorithm in a realistic anatomic geometry torso model (forward problem). Specifically, we investigate the effect of measurement noise, dipole position and electrode configuration in the accuracy of the algorithm. The boundary element method was used to calculate the forward potential distribution at multiple electrode positions on the body surface due to a point dipole in the heart. We have found that the position and not the number of electrodes as well as the site of the origin of the arrhythmia in the heart have a significant effect on the accuracy of the inverse algorithm, while the measurement noise does not. Finally, we have shown that the inverse algorithm preserves the topology of the source distribution in the heart, thus potentially allowing the cardiac electrophysiologist to efficiently and accurately guide the tip of the catheter to the ablation site.

Background: Discussion about the selection of diagnostic features of the ECG and their possible interpretation would benefit from a model of the genesis of these signals that has a sound basis in electrophysiology as well as in physics. Recent advances in computer technology have made it possible to build a simulation package whereby the genesis of ECG signals can be studied interactively., Design: A numerical method was developed for computing ECG signals on the thorax, as well as electrograms on both endocardium and epicardium. The source representation of the myocardial electric activity is the equivalent double layer. The transfer factors between the electric sources and the resulting potentials on the heart surface as well as on the body surface were computed using a realistic thorax model., Results and Conclusion: The resulting transfer factors were implemented in a simulation program. The program allows the user to make interactive changes in the timing of depolarisation and repolarisation on the ventricular surface, as well as changing the local source strength, and to inspect or document the effect of such changes instantaneously on electrograms and body surface potentials, visualised by waveforms as well as by potential maps and movies. The entire simulation package can be installed free of charge from www.ecgsim.org.

ECGSIM is an interactive computer program that solves the forward problem of electrocardiology. The user may set the depolarization and repolarization times at the heart surface, as well as the transmembrane potential amplitude. The program computes the resulting ECGs at the body surface. In this way, the effect of changes of the electric activity of the heart on the ECG can be studied. ECGSIM may be downloaded, free of charge, from the web.

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., (Copyright 2002 Wiley-Liss, Inc.)

The conductivity of the human skull was measured both in vitro and in vivo. The in vitro measurement was performed on a sample of fresh skull placed within a saline environment. For the in vivo measurement a small current was passed through the head by means of two electrodes placed on the scalp. The potential distribution thus generated on the scalp was measured in two subjects for two locations of the current injecting electrodes. Both methods revealed a skull conductivity of about 0.015 [symbol: see text]/m. For the conductivities of the brain, the skull and the scalp a ratio of 1:1/15:1 was found. This is consistent with some of the reports on conductivities found in the literature, but differs considerably from the ratio 1:1/80:1 commonly used in neural source localization. An explanation is provided for this discrepancy, indicating that the correct ratio is 1:1/15:1.

In this study, we investigated the accuracy of an algorithm to identify the spatial single equivalent moving dipole parameters in a realistic anatomic geometry torso model from potentials at the body surface. Specifically we investigated the effect of measurement noise, and dipole position and orientation in the accuracy of the algorithm. The boundary element method was used to calculate the forward potential distribution at 64 electrode positions on the body surface due to a point dipole. The mean and standard deviation of the distance of the true (obtained in the forward potential calculation) minus the estimated dipole location (obtained from the inverse algorithm) was estimated for each of the above three cases. Our results indicate that the dipole position has the most significant influence on the accuracy of our inverse algorithm.

Hyaluronic acid (Healon), oxycellulose (hydroxypropyl methylcellulose), and glycerin are lubricants used in cochlear implant surgery for atraumatic deep insertion of the electrode array into the scala tympani. The electrical impedances of these three lubricants were measured to assess possible effects on intraoperative evoked response measurements, such as the electrically evoked stapedius reflex and auditory brain stem response. The impedances of hyaluronic acid, oxycellulose, and saline were very similar and independent of frequency (20 Hz to 1 MHz). Glycerin had an excessively high impedance at low frequencies. A film of hyaluronic acid or oxycellulose around the electrode array immersed in saline did not have any measurable effect on the impedance; a film of glycerin resulted in a strongly reactive polarized layer. However, neither the far-field current spread nor the impedance between stimulated electrodes was affected by any of the lubricants applied as a thin film. This suggests that none of these lubricants affect intraoperative responses, when applied as a thin film.

The problem of obtaining the retinal source distribution that generates the electroretinogram (ERG) from measured skin potentials is addressed. A realistic three-dimensional (3-D) volume conductor model of the head is constructed from magnetic resonance image (MRI) data sets. The skin potential distribution generated in this model by a dipole layer source at the retina is computed by using the boundary element method (BEM). The influence of the various compartments of the complete model on the results was investigated, and a simplified model was defined. An inverse procedure for estimating the source distribution at the retina from ERG's obtained from skin electrodes was developed. The procedure was tested on simulated potentials. A fair correspondence between the original and estimated source distribution was found. Furthermore, the ERG's measured at seven skin electrodes were used to estimate the source distribution at the retina. The ERG potential waveform at an additional skin electrode was computed from this source distribution and compared to the measured potential at this electrode. Again a fair correspondence was obtained. It is concluded that the methods may become a useful tool for clinical applications, i.e., for the assessment of localized defects in retinal function.

The use of the surface Laplacian of the potential (Ls) in bioelectricity is discussed. Different estimates of Ls, in particular the field measured by coaxial electrodes, are compared to that of the true Laplacian. A method to compute Ls on the surface of an inhomogeneous volume conductor of arbitrary shape resulting from assumed electrical sources in introduced. In two applications the sensitivity of the body surface Laplacian is carried to that of body surface potentials. This comparison is carried out for dipolar sources within the human brain as well as for distributed sources within the heart.

In this paper, a method is described to transform Body Surface Map (BSM) data from one lead system to that of another. This enables pooling of BSM data between different centres. The transformation tool is based upon Laplacian interpolation. It is evaluated by inspecting transformations from lead systems having few leads to one having many leads.

During gestation the abdominally recorded fetal ECG (FECG) changes as a result of changes in the conductive medium. In particular, a minimum occurs in the FECG amplitude around 30 weeks of gestation. Based on the results of an extensive FECG study, the effect of these changes on the fetal MCG are simulated. It is shown that the FMCG amplitude is not greatly affected by the changes in the conductive medium. The FMCG waveform, however, is.

Magnetocardiographic signals, as present outside the thorax and generated by the depolarization process within the ventricles of the human heart, have been computed by using a model that incorporates the uniform double layer as the exclusive primary source. The volume conductor effects are treated by using an inhomogeneous, multicompartmental model of the thorax, based on "tailored" geometry derived from magnetic resonance imaging. The required activation function, specifying the timing of the ventricular depolarization process, was derived from an inverse procedure that uses as input data electric signals measured at the body surface. Next, the magnetic signals from the same subjects were measured. A close correspondence between computed and measured magnetic signals was observed (relative root mean square residual difference of 0.37). These results demonstrate that magnetocardiograms and electrocardiograms have a common basis and that it is unlikely that prominent sources exist that are electrically silent and yet active in the genesis of the magnetic fields associated with the depolarization process of the heart. Moreover, fresh support is implied for the usefulness of the classical uniform double layer as the electrical source model during ventricular depolarization. The contributions of the secondary sources have previously been found to be a major component of the electric signals; they are now also shown to be a major component of the magnetic signals.

The pathways along which the electrical currents generated by the fetal heart are conducted to the surface of the maternal abdomen are not known. As a consequence, in recording the fetal electrocardiogram (FECG) it is hard to predict where electrodes should be placed in order to obtain an optimal signal. The amplitude of the FECG varies with gestation, and there is a large interindividual variability in the amplitude of the FECG and in the optimal recording site among subjects within the same gestational age. Attempts have been made to explain these phenomena in terms of volume conduction. In this research the complete potential distribution on the maternal abdomen is studied in connection with the geometrical configuration of the electrical source (fetal heart) and the volume conductor (surrounding tissues). For a small group of pregnant women the abdominal FECG is recorded simultaneously in 32 leads during a period of about one minute, once every two weeks from 20 weeks of gestation onwards. A spatial filtering technique which combines information of all 32 leads is used to provide a trigger of the fetal QRS complexes. Using this trigger, an average fetal complex is constructed for each lead by time coherent averaging, after subtraction of the maternal contribution. These average fetal complexes are combined to plot the complete potential distribution generated by the fetal heart at the maternal abdomen (fetal body surface map, FBSM) at any given time instant during the fetal cardiac cycle. At these recording sessions the geometry is carefully quantified by making transverse scans every 2 cm with a compound echo scanner. The contours of fetal head and body, the placenta and the uterus are manually drawn on hardcopies of the video display images. Real time echoscopy is used to support the identification of the geometry. The contours are fed into a computer using a graphics tablet. The three dimensional surfaces of fetus, placenta and uterus are separately represented by a triangulation of the respective contour lines. Figures 5 and 6 show an example of the triangulated representation of the recorded geometry. Figure 7 shows the average fetal complexes of an individual at 26 weeks of gestation, plotted at the site where they have been recorded.(ABSTRACT TRUNCATED AT 400 WORDS)

The electrical conduction of the ECG from the fetal heart to the maternal abdomen has been modelled by using volume conductor models based on the measured actual geometry. The models have been verified by means of multi-lead recordings of the fetal ECG. The results show that early in pregnancy (less than 28 weeks) the conduction can successfully be described by an electrically homogeneous model. Based on this model, a description of the fetal ECG that is independent of the position of the fetus is derived. In late pregnancies, the conduction is dominated by the isolating effect of the vernix caseosa. As the distribution of the vernix over the fetal body is unknown, the shape of the fetal ECG is disturbed in an unintelligible way. As a consequence, caution has to be applied when using the shape of the fetal ECG for diagnostic means.

In this paper it is demonstrated that the use of a direct matrix inverse in the solution of the forward problem in volume conduction problems greatly facilitates the application of standard, nonlinear parameter estimation procedures for finding the strength as well as the location of current sources inside an inhomogeneous volume conductor of arbitrary shape from potential measurements at the outer surface (inverse procedure). This, in turn, facilitates the inclusion of a priori constraints. Where possible, the performance of the method is compared to that of the Gabor-Nelson method. Applications are in the fields of bioelectricity (e.g., electrocardiography and electroencephalography).

The results of a study in which multi-lead simultaneous recordings of the abdominal fetal electrocardiogram (FECG) have been made are presented. A homogeneous volume conduction model based on the actual recorded geometry was made. Using this model, fetal vectorcardiograms (FVCGS) were computed. Before 28 weeks of gestation the inter- and intra-individual variability of the observed signals could be removed by computing FVCGs in a fetal reference frame. This opens up the possibility of using the shape of the QRS complex for diagnostic purposes.