Electric Field Model Research Articles

Unipolar induction hypothesis testing experiment

The phenomenon of unipolar induction is closely related to the problem of electrodynamics of rotating reference frames. Attempts to apply the general relativity theory to construct the electrodynamics of rotating systems have not yet led to a universally recognised theory. Various authors derive different systems of electrodynamics equations in rotating reference frames and different models of the electric field of a rotating magnet. These models can be tested in experiments with rotating magnets. In this work, an experiment is performed to test two models of the electric field of a rotating magnetised sphere. The theoretical models predict different values of the electric potential of unipolar induction at the pole and equator of the sphere relative to infinity. In the experiment, direct measurements of the potential of the pole and equator of a rotating magnetised sphere relative to a grounded screen are performed. The experimental results contradict the quadrupole model and correspond to the electric field model obtained by applying Lorenz transformations for the field vectors both inside and outside the sphere.

Mechanistic insights into the thermal–mechanical aging of the interface of cross‐linked polyethylene/silicone rubber

AbstractCable accessory has the interface formed by cross‐linked polyethylene (XLPE)/silicone rubber (SiR), which is prone to surface discharge and thus causes the failure of cable system. This article conducts the simulated experiment of thermal–mechanical aging on the interface of XLPE/SiR. The interfacial breakdown and dielectric properties under different aging states are analyzed. It is found the interfacial aging process of XLPE can be divided into the recrystallization stage and the oxidation reaction stage. The former contributes to the interfacial roughness and thus the better insulating performance, whereas the latter leads to degradation of interface, and thus the worse insulating performance. In addition, combined with the established electric field model for the interface, the differences between thermal–mechanical aging and individual thermal aging on the interface are discussed. The sample under thermal–mechanical aging reaches the maximum interfacial breakdown voltage later than that under individual thermal aging, but their performance tends to be consistent in the later stage of aging.

Predicting the hotspot location and motor threshold prior to transcranial magnetic stimulation using electric field modelling

Objective. To investigate whether the motor threshold (MT) and the location of the motor hotspot in transcranial magnetic stimulation (TMS) can be predicted with computational models of the induced electric field. Approach. Individualized computational models were constructed from structural magnetic resonance images of ten healthy participants, and the induced electric fields were determined with the finite element method. The models were used to optimize the location and direction of the TMS coil on the scalp to produce the largest electric field at a predetermined cortical target location. The models were also used to predict how the MT changes as the magnetic coil is moved to various locations over the scalp. To validate the model predictions, the motor evoked potentials were measured from the first dorsal interosseous (FDI) muscle with TMS in the ten participants. Both computational and experimental methods were preregistered prior to the experiments. Main results. Computationally optimized hotspot locations were nearly as accurate as those obtained using manual hotspot search procedures. The mean Euclidean distance between the predicted and the measured hotspot locations was approximately 1.3 cm with a 0.8 cm bias towards the anterior direction. Exploratory analyses showed that the bias could be removed by changing the cortical target location that was used for the prediction. The results also indicated a statistically significant relationship (p < 0.001) between the calculated electric field and the MT measured at several locations on the scalp. Significance. The results show that the individual TMS hotspot can be located using computational analysis without stimulating the subject or patient even once. Adapting computational modelling would save time and effort in research and clinical use of TMS.

Transcranial direct current stimulation as treatment for major depression in a home treatment setting (HomeDC trial): study protocol and methodology of a double-blind, placebo-controlled pilot study

IntroductionTranscranial direct current stimulation (tDCS) of prefrontal cortex regions has been reported to exert therapeutic effects in patients with major depressive disorder (MDD). Due to its beneficial safety profile, its easy mode of application, and its cost-effectiveness, tDCS has recently been proposed for treatment at home. This would offer new chances for regionally widespread and long-term application. However, tDCS at home must meet the new methodological challenges of handling and adherence. At the same time, data from randomized controlled trials (RCT) investigating this mode of application are still lacking. In this pilot RCT, we therefore investigate the feasibility, safety, and effectiveness of a new antidepressant tDCS application set-up.Methods and analysisThe HomeDC trial will be conducted as a double-blind, placebo-controlled, parallel-group design trial. Thirty-two study participants with MDD will be randomly assigned to active or sham tDCS groups. Participants will self-administer prefrontal tDCS for 6 weeks. Active tDCS will be conducted with anode over F3, cathode over F4, for 5 sessions/week, with a duration of 30 min/day, and 2 mA stimulation intensity. Sham tDCS, conversely, follows an identical protocol in regard to electrode montage and timing, but with no electric stimulation between the ramp-in and ramp-out periods. Both conditions will be administered either as a monotherapy or an adjunctive treatment to a stable dose of antidepressant medication. Adjunctive magnetic resonance imaging (MRI) and electric field (E-field) modelling will be conducted at baseline. Primary outcome is feasibility based on successfully completed stimulations and drop-out rates. The intervention is considered feasible when 20 out of 30 sessions have been fully conducted by at least 75% of the participants. Effectiveness and safety will be assessed as secondary outcomes.DiscussionIn the HomeDC trial, the technical requirements for a placebo-controlled tDCS study in a home-based treatment setting have been established. The trial addresses the crucial points of the home-based tDCS treatment approach: uniform electrode positioning, frequent monitoring of stimulation parameters, adherence, and ensuring an appropriate home treatment environment. This study will further identify constraints and drawbacks of this novel mode of treatment.Trial registrationwww.ClinicalTrials.gov. Trial registration number: NCT05172505. Registration date: 12/13/2021.

Predicting of spatial electric field generated by substation switch operation based on AOS-GCN-LSTM Model

The radiation of adjacent field sources has a specific spatial correlation. In order to suppress electromagnetic disturbance and improve the electromagnetic compatibility of secondary equipment, the electric field’s spatial coupling characteristics and distribution law should be mastered. Therefore, a method for predicting the spatial electric field generated by substation switching operation based on the Atomic Orbital Search-Graph Convolution Network- Long and Short-Term Memory (AOS-GCN-LSTM) model is presented to deal with this problem. First, the GCN is used to construct graph data according to node characteristics and topology information. The feature selection uses the Maximum Information Coefficient (MIC) to extract the spatial correlation of the adjacent field source radiation. At the same time, the LSTM is used to capture the temporal correlation characteristics of different position field strengths in space. Then, the AOS is used to optimize the model with a hyperparameter. In addition, the simulation data of the full-wave simulation model of the spatial electric field generated by switch operation in a 220 kV GIS substation is an example of verification. The results show that the prediction error of the proposed method is below 3%, and it has strong adaptability to the application environment and good prediction performance.

Improved Harmonic Model Method for Electrical Machine Magnetic Field Modeling

Improved Harmonic Model Method for Electrical Machine Magnetic Field Modeling

Towards an optimised deep brain stimulation using a large-scale computational network and realistic volume conductor model

Objective. Constructing a theoretical framework to improve deep brain stimulation (DBS) based on the neuronal spatiotemporal patterns of the stimulation-affected areas constitutes a primary target. Approach. We develop a large-scale biophysical network, paired with a realistic volume conductor model, to estimate theoretically efficacious stimulation protocols. Based on previously published anatomically defined structural connectivity, a biophysical basal ganglia-thalamo-cortical neuronal network is constructed using Hodgkin–Huxley dynamics. We define a new biomarker describing the thalamic spatiotemporal activity as a ratio of spiking vs. burst firing. The per cent activation of the different pathways is adapted in the simulation to minimise the differences of the biomarker with respect to its value under healthy conditions. Main results. This neuronal network reproduces spatiotemporal patterns that emerge in Parkinson’s disease. Simulations of the fibre per cent activation for the defined biomarker propose desensitisation of pallido-thalamic synaptic efficacy, induced by high-frequency signals, as one possible crucial mechanism for DBS action. Based on this activation, we define both an optimal electrode position and stimulation protocol using pathway activation modelling. Significance. A key advantage of this research is that it combines different approaches, i.e. the spatiotemporal pattern with the electric field and axonal response modelling, to compute the optimal DBS protocol. By correlating the inherent network dynamics with the activation of white matter fibres, we obtain new insights into the DBS therapeutic action.

The impact of brain lesions on tDCS-induced electric fields

Transcranial direct current stimulation (tDCS) can enhance motor and language rehabilitation after stroke. Though brain lesions distort tDCS-induced electric field (E-field), systematic accounts remain limited. Using electric field modelling, we investigated the effect of 630 synthetic lesions on E-field magnitude in the region of interest (ROI). Models were conducted for two tDCS montages targeting either primary motor cortex (M1) or Broca’s area (BA44). Absolute E-field magnitude in the ROI differed by up to 42% compared to the non-lesioned brain depending on lesion size, lesion-ROI distance, and lesion conductivity value. Lesion location determined the sign of this difference: lesions in-line with the predominant direction of current increased E-field magnitude in the ROI, whereas lesions located in the opposite direction decreased E-field magnitude. We further explored how individualised tDCS can control lesion-induced effects on E-field. Lesions affected the individualised electrode configuration needed to maximise E-field magnitude in the ROI, but this effect was negligible when prioritising the maximisation of radial inward current. Lesions distorting tDCS-induced E-field, is likely to exacerbate inter-individual variability in E-field magnitude. Individualising electrode configuration and stimulator output can minimise lesion-induced variability but requires improved estimates of lesion conductivity. Individualised tDCS is critical to overcome E-field variability in lesioned brains.

What determines the rest frame of bubble nucleation?

We revisit the question addressed in recent papers by Garriga et al.: what determines the rest frame of pair nucleation in a constant electric field? The conclusion reached in these papers is that pairs are observed to nucleate at rest in the rest frame of the detector which is used to detect the pairs. A similar conclusion should apply to bubble nucleation in a false vacuum. This conclusion however is subject to doubt due to the unphysical nature of the model of a constant eternal electric field that was used by Garriga et al. The number density of pairs in such a field would be infinite at any finite time. Here we address the same question in a more realistic model where the electric field is turned on at a finite time t 0 in the past. The process of turning on the field breaks the Lorentz invariance of the model and could in principle influence the frame of pair nucleation. We find however that the conclusion of Garriga et al. still holds in the limit t 0 → -∞. This shows that the setup process of the electric field does not have a lasting effect on the observed rest frame of pair nucleation. On the other hand, the electric current and charge density due to the pairs are determined by the way in which the electric field was turned on.

White matter connectivity of subthalamic nucleus and globus pallidus interna targets for deep brain stimulation.

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) and globus pallidus interna (GPi) have differential therapeutic effects for Parkinson's disease (PD) that drive patient selection. For example, GPi DBS is preferred for dystonic features and dyskinesia, whereas STN DBS has shown faster tremor control and medication reduction. Connectivity studies comparing these two targets, using patient-specific data, are still lacking. The objective was to find STN and GPi structural connectivity patterns in order to better understand differences in DBS-activated brain circuits between these two stimulation targets and to guide optimal contact selection. The authors simulated DBS activation along the main axis of both the STN and GPi by using volume of activated tissue (VAT) modeling with known average stimulation parameters (2.8 V and 60 μsec for STN; 3.3 V and 90 μsec for GPi). The authors modeled VATs in the anterior, middle, and posterior STN and the anterior, midanterior, midposterior, and posterior GPi. The authors generated maps of the connections shared by the patients for each VAT by using probabilistic tractography of diffusion-weighted imaging data obtained in 46 PD patients who underwent DBS (26 with STN and 20 with GPi targeting), and differences between VATs for whole-brain and distal regions of interest (prefrontal cortex, supplementary motor area, primary motor cortex, primary sensory cortex, caudate, motor thalamus, and cerebellum) were generated from structural atlases. Differences between maps were quantified and compared. VATs across the STN and GPi had different structural connectivity patterns. The authors found significant connectivity differences between VATs for all regions of interest. Posterior and middle STN showed stronger connectivity to the primary motor cortex and supplementary motor area (SMA) (p < 0.001). Posterior STN had the strongest connectivity to the primary sensory cortex and motor thalamus (p < 0.001). Posterior GPi showed stronger connectivity to the primary motor cortex (p < 0.001). Connectivity to the SMA was similar for the posterior and midposterior GPi (p > 0.05), which was greater than that for the anterior GPi (p < 0.001). When both nuclei were compared, posterior and middle STN had stronger connectivity to the SMA, cerebellum, and motor thalamus than GPi (all p < 0.001). Posterior GPi and STN had similar connectivity to the primary sensory cortex. On patient-specific imaging, structural connectivity differences existed between GPi and STN DBS, as measured with standardized electrical field modeling of the DBS targets. These connectivity differences may correlate with the differential clinical benefits obtained by targeting each of the two nuclei with DBS for PD. Prospective work is needed to relate these differences to clinical outcomes and to inform targeting and programming.

Differences in the Electric Field Distribution Predicted with a Mathematical Model of Cylindrical Electrodes of Finite Length vs. Infinite Length: A Comparison Based on Analytical Solution

Cylindrical-shaped metal electrodes are used in numerous medical specialties to force an electric field into the surrounding tissue (e.g., in electrical stimulation and electroporation). Although these electrodes have a limited length in reality, previous mathematical modeling studies have simplified the physical situation and have built a model geometry based on a cylindrical electrode of infinite length, which allows for reducing the model from 2D to 1D. Our objective was to quantify the differences in the electric field values between the finite and infinite electrode cases and assess the adequacy of the mentioned simplification for different values of electrode diameter and length. We used analytical solutions for the electric field distribution. We found that the electric field distribution is substantially different for both cases, not only near the edges of the electrode (when finite length is assumed) and in close locations (&lt;1 mm), but even in the central area and at distances greater than 2 mm. Our work presents analytical solutions for both cases (finite and infinite length), which, despite the oscillations derived from computational limitations, could be used by researchers involved in electric field modeling in biological tissues, in order to quantify the possible error generated with simple models in geometric terms that assume infinite length.

Modeling the effects of transcranial magnetic stimulation on spatial attention

Objectives. Transcranial magnetic stimulation (TMS) has been widely used to modulate brain activity in healthy and diseased brains, but the underlying mechanisms are not fully understood. Previous research leveraged biophysical modeling of the induced electric field (E-field) to map causal structure–function relationships in the primary motor cortex. This study aims at transferring this localization approach to spatial attention, which helps to understand the TMS effects on cognitive functions, and may ultimately optimize stimulation schemes. Approach. Thirty right-handed healthy participants underwent a functional magnetic imaging (fMRI) experiment, and seventeen of them participated in a TMS experiment. The individual fMRI activation peak within the right inferior parietal lobule (rIPL) during a Posner-like attention task defined the center target for TMS. Thereafter, participants underwent 500 Posner task trials. During each trial, a 5-pulse burst of 10 Hz repetitive TMS (rTMS) was given over the rIPL to modulate attentional processing. The TMS-induced E-fields for every cortical target were correlated with the behavioral modulation to identify relevant cortical regions for attentional orientation and reorientation. Main results. We did not observe a robust correlation between E-field strength and behavioral outcomes, highlighting the challenges of transferring the localization method to cognitive functions with high neural response variability and complex network interactions. Nevertheless, TMS selectively inhibited attentional reorienting in five out of seventeen subjects, resulting in task-specific behavioral impairments. The BOLD-measured neuronal activity and TMS-evoked neuronal effects showed different patterns, which emphasizes the principal distinction between the neural activity being correlated with (or maybe even caused by) particular paradigms, and the activity of neural populations exerting a causal influence on the behavioral outcome. Significance. This study is the first to explore the mechanisms of TMS-induced attentional modulation through electrical field modeling. Our findings highlight the complexity of cognitive functions and provide a basis for optimizing attentional stimulation protocols.

Developing checkerboard cross element metasurface with multi-Fano response for sensing in the infrared spectrum

A novel metasurface has been developed based on a checkerboard formation for optical biosensing in the infrared spectrum (10 μm) to diagnose cancer cells in the early stages. The design incorporates phase control in each quarter of the checkerboard metasurface to achieve Fano and mufti Fano responses. The resonances are provided by a self-similar arrangement of cross elements. The interaction between these elements enables hybridization between bright modes, resulting in both bright and dark modes to produce the desired Fano response. The final structure exhibits a quad-band Fano response, and the four steps of the design process are presented and discussed. The physics behind the proposed metasurface is described using the electric field and circuit model. The designed structure is optimized for the frequency range of 10–40 THz. The sensitivity, Q-factor, and Figure of Merit (FOM) are examined for each resonance to evaluate the material under test. The extracted results demonstrate that the proposed metasurface allows for the identification of unknown materials with higher accuracy compared to conventional metasurfaces with a single resonance. The maximum Q-factor achieved is approximately 354, and the maximum FOM is obtained at 47.4 RIU−1. Additionally, the sensitivity factor reaches a maximum value of 3657 nm/RIU, further enhancing the sensing capabilities of the metasurface.

Non-invasive temporal interference electrical stimulation of the human hippocampus

Deep brain stimulation (DBS) via implanted electrodes is used worldwide to treat patients with severe neurological and psychiatric disorders. However, its invasiveness precludes widespread clinical use and deployment in research. Temporal interference (TI) is a strategy for non-invasive steerable DBS using multiple kHz-range electric fields with a difference frequency within the range of neural activity. Here we report the validation of the non-invasive DBS concept in humans. We used electric field modeling and measurements in a human cadaver to verify that the locus of the transcranial TI stimulation can be steerably focused in the hippocampus with minimal exposure to the overlying cortex. We then used functional magnetic resonance imaging and behavioral experiments to show that TI stimulation can focally modulate hippocampal activity and enhance the accuracy of episodic memories in healthy humans. Our results demonstrate targeted, non-invasive electrical stimulation of deep structures in the human brain.

Evolution of the Interelectrode Gap during Co-Rotating Electrochemical Machining

A new co-rotating electrochemical machining method is presented to machine the complex structure inside annular parts such as flame tubes and aero-engine casings. Due to the unique shape and motion of electrodes, it is difficult to accurately compute the electric field intensity in the machining area. In this paper, the complex electric field model is simplified by conformal transformation, and the analytical solution of electric field intensity is exactly calculated. A material removal model is built on the basis of the electric field model, and the dynamic simulation of the material removal process is realized. The effects of the cathode radius, applied voltage, feed rate and initial interelectrode gap on the interelectrode gap (IEG) and material removal rate (MRR) are analyzed. The simulation results indicate that the MRR is always slightly less than the feed rate in a quasi-equilibrium state, resulting in a slow reduction in IEG. In addition, the final machining state is not affected by the initial IEG, and the MRR in a quasi-equilibrium state is determined by the feed rate. Several comparative experiments were carried out using the optimized processing parameters, in which the MRR and IEG were measured. The convex structures were successfully machined inside the annular workpiece with optimum machining parameters. The experimental results are in good agreement with the theoretical results, indicating that the established model can effectively predict the evolution process of MRR and IEG.

Integrating electric field modeling and pre-tDCS behavioral performance to predict the individual tDCS effect on visual crowding

Objective. Transcranial direct current stimulation (tDCS) has been broadly used to modulate brain activity with both bipolar and high-definition montages. However, tDCS effects can be highly variable. In this work, we investigated whether the variability in the tDCS effects could be predicted by integrating individualized electric field modeling and individual pre-tDCS behavioral performance. Approach. Here, we first compared the effects of bipolar tDCS and 4 × 1 high-definition tDCS (HD-tDCS) with respect to the alleviation of visual crowding, which is the inability to identify targets in the presence of nearby flankers and considered to be an essential bottleneck of object recognition and visual awareness. We instructed subjects to perform an orientation discrimination task with both isolated and crowded targets in the periphery and measured their orientation discrimination thresholds before and after receiving 20 min of bipolar tDCS, 4 × 1 HD-tDCS, or sham stimulation over the visual cortex. Individual anatomically realistic head models were constructed to simulate tDCS-induced electric field distributions and quantify tDCS focality. Finally, a multiple linear regression model that used pre-tDCS behavioral performance and tDCS focality as factors was used to predict post-tDCS behavioral performance. Main results. We found that HD-tDCS, but not bipolar tDCS, could significantly alleviate visual crowding. Moreover, the variability in the tDCS effect could be reliably predicted by subjects’ pre-tDCS behavioral performance and tDCS focality. This prediction model also performed well when generalized to other two tDCS protocols with a different electrode size or a different stimulation intensity. Significance. Our study links the variability in the tDCS-induced electric field and the pre-tDCS behavioral performance in a visual crowding task to the variability in post-tDCS performance. It provides a new approach to predicting individual tDCS effects and highlights the importance of understanding the factors that determine tDCS effectiveness while developing more robust protocols.

Interconnected square splits ring resonator based single negative metamaterial for 5G (N258, N257, N260 and N259) band sensor/EMI shielding/and antenna applications

This article proposed a new triple-band transmission block metamaterial (MTM) for 5G mm-wave applications. The peak transmission-blocking attributes are achieved at 27.09 GHz, 38.71 GHz, and 41.81 GHz frequency by interconnected square split ring resonators (ISSRR). A thin Rogers RT5880 substrate material of thickness 0.79 mm is employed to design the MTM structure, and the unit cell dimension is 5 × 5 mm2. The designed metamaterial shows a −10 dB transmission coefficient (S21) from 24.60 to 28.47 GHz, 36.50–39.65 GHz and 40.77–44 GHz frequency bands. The design evolution, metamaterial properties, surface current distribution, electric field, magnetic field, and equivalent circuit model are investigated to understand the transmission-blocking property of the MTM. The simulated results of the MTM are validated by measurement of the fabricated prototype, and both results agree well. The transmission-blocking attributes lead the proposed MTM as a potential candidate for different fields like EMI shielding, sensing, and antenna performance enhancement. The dielectric sensor performance of the MTM structure is investigated for different dielectric materials. Besides, MIMO antenna performances are also investigated, and gains of 1–3 dBi, isolations of 5–10 dB, and the radiation pattern deflection angle of 45˚ are enhanced by the proposed MTM. These significant features and applications of the proposed MTM make it a special candidate for 5G mm-wave applications.

Outcome measures for electric field modeling in tES and TMS: A systematic review and large-scale modeling study

BackgroundElectric field (E-field) modeling is a potent tool to estimate the amount of transcranial magnetic and electrical stimulation (TMS and tES, respectively) that reaches the cortex and to address the variable behavioral effects observed in the field. However, outcome measures used to quantify E-fields vary considerably and a thorough comparison is missing. ObjectivesThis two-part study aimed to examine the different outcome measures used to report on tES and TMS induced E-fields, including volume- and surface-level gray matter, region of interest (ROI), whole brain, geometrical, structural, and percentile-based approaches. The study aimed to guide future research in informed selection of appropriate outcome measures. MethodsThree electronic databases were searched for tES and/or TMS studies quantifying E-fields. The identified outcome measures were compared across volume- and surface-level E-field data in ten tES and TMS modalities targeting two common targets in 100 healthy individuals. ResultsIn the systematic review, we extracted 308 outcome measures from 202 studies that adopted either a gray matter volume-level (n = 197) or surface-level (n = 111) approach. Volume-level results focused on E-field magnitude, while surface-level data encompassed E-field magnitude (n = 64) and normal/tangential E-field components (n = 47). E-fields were extracted in ROIs, such as brain structures and shapes (spheres, hexahedra and cylinders), or the whole brain. Percentiles or mean values were mostly used to quantify E-fields. Our modeling study, which involved 1,000 E-field models and > 1,000,000 extracted E-field values, revealed that different outcome measures yielded distinct E-field values, analyzed different brain regions, and did not always exhibit strong correlations in the same within-subject E-field model. ConclusionsOutcome measure selection significantly impacts the locations and intensities of extracted E-field data in both tES and TMS E-field models. The suitability of different outcome measures depends on the target region, TMS/tES modality, individual anatomy, the analyzed E-field component and the research question. To enhance the quality, rigor, and reproducibility in the E-field modeling domain, we suggest standard reporting practices across studies and provide four recommendations.

Template MRI scans reliably approximate individual and group-level tES and TMS electric fields induced in motor and prefrontal circuits.

Electric field (E-field) modeling is a valuable method of elucidating the cortical target engagement from transcranial magnetic stimulation (TMS) and transcranial electrical stimulation (tES), but it is typically dependent on individual MRI scans. In this study, we systematically tested whether E-field models in template MNI-152 and Ernie scans can reliably approximate group-level E-fields induced in N = 195 individuals across 5 diagnoses (healthy, alcohol use disorder, tobacco use disorder, anxiety, depression). We computed 788 E-field models using the CHARM-SimNIBS 4.0.0 pipeline with 4 E-field models per participant (motor and prefrontal targets for TMS and tES). We additionally calculated permutation analyses to determine the point of stability of E-fields to assess whether the 152 brains represented in the MNI-152 template is sufficient. Group-level E-fields did not significantly differ between the individual vs. MNI-152 template and Ernie scans for any stimulation modality or location (p > 0.05). However, TMS-induced E-field magnitudes significantly varied by diagnosis; individuals with generalized anxiety had significantly higher prefrontal and motor E-field magnitudes than healthy controls and those with alcohol use disorder and depression (p < 0.001). The point of stability for group-level E-field magnitudes ranged from 42 (motor tES) to 52 participants (prefrontal TMS). MNI-152 and Ernie models reliably estimate group-average TMS and tES-induced E-fields transdiagnostically. The MNI-152 template includes sufficient scans to control for interindividual anatomical differences (i.e., above the point of stability). Taken together, using the MNI-152 and Ernie brains to approximate group-level E-fields is a valid and reliable approach.

Low Albumin Determination as a Biomarker Cancer with Cyclic Voltammetry in Agfilm/ITO and AgNOfilm/ITO Electrodes

Ag and AgNO film were fabricated through sputter deposition on indium tin oxide (ITO) conductive glass. Electrochemical detection using cyclic voltammetry (CV) was carried out for low albumin levels in blood as a parameter of cancer patients. This study aims to determinate low albumin level as a biomarker cancer. Albumin adsorption on the Agfilm/ITO and AgNOfilm/ITO was also investigated to determine the level of sensitivity of both electrodes. Analysis of the CV measurements indicated that the Agfilm/ITO electrode was more sensitive compared to the AgNOfilm/ITO electrode, with a sensitivity value of 4.564 µA M-1cm-2 for the Agfilm/ITO electrode and 2.123 µA M-1cm-2 for the AgNOfilm/ITO electrode. The testing of albumin levels in blood within a range of low concentration levels between 10-1 and 10-8 g/dL indicated a detection limit of 10-9 g/mL. The selectivity of Ag electrodes was found to be very good for other interfering molecules such as urine, glucose, and lysozyme. The results of the modeling of electric field and magnetic field distribution showed that the Agfilm/ITO electrode possessed larger values than the AgNOfilm/ITO electrode. From this analysis, it can be concluded that the electrode modified with micro-sized Ag achieved more effective results than the electrode modified with AgNO. This sensor can determine low albumin level as a blood cancer biomarker. This sensor holds great promise for use in real samples in the future. HIGHLIGHTS Early detection with albumin biomarkers before metastasis cancer The testing of albumin levels with Cyclic Voltammetry and Electric Impedance Spectroscopy in the cancer within a wide range of low concentration levels (10-1 - 10-8) indicated a detection limit of 10-9 g/mL. The total mass of adsorbed BSA in electrode surface is more higher (281 mgm-2) than previous study. The Agfilm/ITO electrode exhibited high sensitivity and long-term stability for future applications. GRAPHICAL ABSTRACT