Coil Orientation Research Articles

Advanced Technology or Manual Skills: Evidence That The Accuracy of Corticospinal Responsiveness Is Not Ameliorated by Neuronavigation

PurposeTranscranial magnetic stimulation (TMS) is a noninvasive technique to assess corticospinal excitability and inhibition. TMS over the motor cortex during a voluntary contraction elicits short‐latency excitatory (motor‐evoked potential, MEP) and inhibitory (silent period, SP) responses in the target muscle. However, the technique for searching and determining the optimal site to elicit MEPs (“hotspot”), an essential component in order to correctly place the TMS coil, is not unanimously standardized. This can be a problem since changes in coil position and/or orientation may influence the magnitude of MEP and SP responses. Usually, the “hotspot” is marked either on a swim cap or on the scalp and the investigator holds the coil manually during the entire testing session. However, the capacity to maintain the coil placement within and between sessions may be limited. To reduce variability in coil position and orientation in space and over time, neuronavigated TMS (nTMS) is used. However, no studies investigated the accuracy of the assessment of corticospinal excitability and inhibition using nTMS versus a traditional manual approach for the maintenance of coil positioning.Methods18 healthy participants (10W/8M) volunteered in two identical and randomized sessions ~30 days apart. Maximal and submaximal neuromuscular evaluations were performed with TMS six times before (PRE), and at the end (POST) of a 2‐min sustained maximal voluntary isometric contraction (MVIC) (100%, 75%, 50% MVIC and 25%isoEMG). The “hotspot” was maintained either with a grid demarcated on the participants’ scalp or with visual feedback provided by nTMS on a computer screen. In both sessions, “hotspot” was considered as the site where the largest MEPs in the rectus femoris were elicited.ResultsThere were not a “hotspot” technique × contraction intensities × time points interactions for both MEP (P = 0.217) and SP (P = 0.627). Bland‐Altman plots display adequate agreements between the difference in the two “hotspot” techniques and the means of the two “hotspot” techniques. The slopes of the resulting regression lines were not significantly different from zero (horizontal to x‐axis) for both MEP (all r ≤ 0.335, all P ≥ 0.162) and SP (all r ≤ 0.382, all P ≥ 0.131), indicating a uniformity of systematic error at all contraction intensities and time points.ConclusionsSpatial stability of the TMS coil position over the motor cortex did not influence corticospinal excitability and inhibition responses in unfatigued and fatigued knee extensors. This is because the variability in MEP and SP responses is due to spontaneous fluctuations in corticospinal and motoneuron excitability and inhibition; and this variability is not affected by spatial accuracy. Therefore, nTMS or a traditional manual approach could be interchangeably use in order to maintain the TMS coil position in the exact “hotspot”.

TAP: targeting and analysis pipeline for optimization and verification of coil placement in transcranial magnetic stimulation

Objective. Transcranial magnetic stimulation (TMS) can modulate brain function via an electric field (E-field) induced in a brain region of interest (ROI). The ROI E-field can be computationally maximized and set to match a specific reference using individualized head models to find the optimal coil placement and stimulus intensity. However, the available software lacks many practical features for prospective planning of TMS interventions and retrospective evaluation of the experimental targeting accuracy. Approach. The TMS targeting and analysis pipeline (TAP) software uses an MRI/fMRI-derived brain target to optimize coil placement considering experimental parameters such as the subject’s hair thickness and coil placement restrictions. The coil placement optimization is implemented in SimNIBS 3.2, for which an additional graphical user interface (TargetingNavigator) is provided to visualize/adjust procedural parameters. The coil optimization process also computes the E-field at the target, allowing the selection of the TMS device intensity setting to achieve specific E-field strengths. The optimized coil placement information is prepared for neuronavigation software, which supports targeting during the TMS procedure. The neuronavigation system can record the coil placement during the experiment, and these data can be processed in TAP to quantify the accuracy of the experimental TMS coil placement and induced E-field. Main results. TAP was demonstrated in a study consisting of three repetitive TMS sessions in five subjects. TMS was delivered by an experienced operator under neuronavigation with the computationally optimized coil placement. Analysis of the experimental accuracy from the recorded neuronavigation data indicated coil location and orientation deviations up to about 2 mm and 2°, respectively, resulting in an 8% median decrease in the target E-field magnitude compared to the optimal placement. Significance. TAP supports navigated TMS with a variety of features for rigorous and reproducible stimulation delivery, including planning and evaluation of coil placement and intensity selection for E-field-based dosing.

Systematic numerical assessment of occupational exposure to electromagnetic fields of transcranial magnetic stimulation.

PurposeThis study aims to perform a classification and rigorous numerical evaluation of the risks of occupational exposure in the health environment related to the administration of transcranial magnetic stimulation (TMS) treatment. The study investigates the numerically estimated induced electric field that occurs in the human tissues of an operator caused by exposure to the variable magnetic field produced by TMS during treatments. This could be a useful starting point for future risk assessment studies and safety indications in this context.MethodsWe performed a review of the actual positions assumed by clinicians during TMS treatments. Three different TMS coils (two circular and one figure‐of‐eight) were modeled and characterized numerically. Different orientations and positions of each coil with respect to the body of the operator were investigated to evaluate the induced electric (‐E) field in the body tissues. The collected data were processed to allow comparison with the safety standards for occupational exposure, as suggested by the International Commission on Non‐Ionizing Radiation Protection (ICNIRP) 2010 guidelines.ResultsUnder the investigated conditions, exposure to TMS shows some criticalities for the operator performing the treatment. Depending on the model of the TMS coil and its relative position with respect to the operator's body, the numerically estimated E‐field could exceed the limits suggested by the ICNIRP 2010 guidelines. We established that the worst‐case scenario for the three coils occurs when they are placed in correspondence of the abdomen, with the handle oriented parallel to the body (II orientation). Working at a maximum TMS stimulator output (MSO), the induced E‐field is up to 7.32 V/m (circular coil) and up to 1.34 V/m (figure‐of‐eight coil). The induced E‐field can be modulated by the TMS percentage of MSO (%MSO) and by the distance between the source and the operator. At %MSO equal to or below 80%, the figure‐of‐eight coil was compliant with the ICNIRP limit (1.13 V/m). Conversely, the circular coil causes an induced E‐field above the limits, even when powered at a %MSO of 30%. Thus, in the investigated worst‐case conditions, an operator working with a circular coil should keep a distance from its edge to be compliant with the guidelines limit, which depends on the selected %MSO: 38 cm at 100%, 32 cm at 80%, 26.8 cm at 50%, and 19.8 cm at 30%. Furthermore, attention should be paid to the induced E‐field reached in the operator's hand as the operator typically holds the coil by hand. In fact in the hand, we estimated an induced E‐field up to 10 times higher than the limits.ConclusionsOur numerical results indicate that coil positions, orientations, and distances with respect to the operator's body can determine the levels of induced E‐field that exceed the ICNIRP limits. The induced E‐field is also modulated by the choice of %MSO, which is related to the TMS application. Even under the best exposure conditions, attention should be paid to the exposure of the hand. These findings highlight the need for future risk assessment studies to provide more safety information for the correct and safe use of TMS devices.

Proactive inhibition is marked by differences in the pattern of motor cortex activity during movement preparation and execution.

Successful human behavior relies on the ability to flexibly alter movements depending on the context in which they are made. One such context-dependent modulation is proactive inhibition, a type of behavioral inhibition used when anticipating the need to stop or change movements. We investigated how the motor cortex might prepare and execute movements made under different contexts. We used transcranial magnetic stimulation (TMS) in different coil orientations [postero-anterior (PA) and antero-posterior (AP) flowing currents] and pulse widths (120 and 30 µs) to probe the excitability of different inputs to corticospinal neurons while participants performed two reaction time tasks: a simple reaction time task and a stop-signal task requiring proactive inhibition. We took inspiration from state space models to assess whether the pattern of motor cortex activity changed due to proactive inhibition (PA and AP neuronal circuits represent the x and y axes of a state space upon which motor cortex activity unfolds during motor preparation and execution). We found that the rise in motor cortex excitability was delayed when proactive inhibition was required. State space visualizations showed altered patterns of motor cortex activity (combined PA120 and AP30 activity) during proactive inhibition, despite adjusting for reaction time. Overall, we show that the pattern of neural activity generated by the motor cortex during movement preparation and execution is dependent upon the context under which the movement is to be made.NEW & NOTEWORTHY Using directional TMS, we find that the human motor cortex flexibly changes its pattern of neural activity depending on the context in which a movement is due to be made. Interestingly, this occurs despite adjusting for reaction time. We also show that state space and dynamical systems models of movement can be noninvasively visualized in humans using TMS, thereby offering a novel method to study these powerful models in humans.

TMS intensity and focality correlation with coil orientation at three non-motor regions

Objective. The aim of this study is to define the best coil orientations for transcranial magnetic stimulation (TMS) for three clinically relevant brain areas: pre-supplementary motor area (pre-SMA), inferior frontal gyrus (IFG), and posterior parietal cortex (PPC), by means of simulations in 12 realistic head models of the electric field (E-field). Methods. We computed the E-field generated by TMS in our three volumes of interest (VOI) that were delineated based on published atlases. We then analysed the maximum intensity and spatial focality for the normal and absolute components of the E-field considering different percentile thresholds. Lastly, we correlated these results with the different anatomical properties of our VOIs. Results. Overall, the spatial focality of the E-field for the three VOIs varied depending on the orientation of the coil. Further analysis showed that differences in individual brain anatomy were related to the amount of focality achieved. In general, a larger percentage of sulcus resulted in better spatial focality. Additionally, a higher normal E-field intensity was achieved when the coil axis was placed perpendicular to the predominant orientations of the gyri of each VOI. A positive correlation between spatial focality and E-field intensity was found for PPC and IFG but not for pre-SMA. Conclusions. For a rough approximation, better coil orientations can be based on the individual’s specific brain morphology at the VOI. Moreover, TMS computational models should be employed to obtain better coil orientations in non-motor regions of interest. Significance. Finding better coil orientations in non-motor regions is a challenge in TMS and seeks to reduce interindividual variability. Our individualized TMS simulation pipeline leads to fewer inter-individual variability in the focality, likely enhancing the efficacy of the stimulation and reducing the risk of stimulating adjacent, non-targeted areas.

Using machine learning to predict optimal electromagnetic induction instrument configurations for characterizing the shallow subsurface

Abstract. Electromagnetic induction (EMI) is used widely for hydrological and other environmental studies. The apparent electrical conductivity (ECa), which can be mapped efficiently with EMI, correlates with a variety of important soil attributes. EMI instruments exist with several configurations of coil spacing, orientation, and height. There are general, rule-of-thumb guides to choose an optimal instrument configuration for a specific survey. The goal of this study was to provide a robust and efficient way to design this optimization task. In this investigation, we used machine learning (ML) as an efficient tool for interpolating among the results of many forward model runs. Specifically, we generated an ensemble of 100 000 EMI forward models representing the responses of many EMI configurations to a range of three-layer subsurface models. We split the results into training and testing subsets and trained a decision tree (DT) with gradient boosting (GB) to predict the subsurface properties (layer thicknesses and EC values). We further examined the value of prior knowledge that could limit the ranges of some of the soil model parameters. We made use of the intrinsic feature importance measures of machine learning algorithms to identify optimal EMI designs for specific subsurface parameters. The optimal designs identified using this approach agreed with those that are generally recognized as optimal by informed experts for standard survey goals, giving confidence in the ML-based approach. The approach also offered insight that would be difficult, if not impossible, to offer based on rule-of-thumb optimization. We contend that such ML-informed design approaches could be applied broadly to other survey design challenges.

Utilising angle-dependent critical current data in the electromagnetic modelling of HTS coils

A detailed methodology is presented for modelling the electromagnetic characteristics of HTS coils using angle-dependent critical current data obtained from experimental measurements of real wire samples. The results of such an analysis are contrasted with those obtained using more prevalent approaches such as a global minimum critical current method or an elliptical field magnitude-dependent functional approximation. Several interesting design consequences of significance to real-world devices that emerge only when the full anisotropy of real wires is taken into account are outlined and discussed. These include the beneficial impact on various performance metrics of the adoption of mixed conductor windings, the importance of coil orientation in optimising device performance, and the potential opportunity to derive a specific design benefit from the targeted use of conductors possessing inclined planarity.

Effect of Helical Coil Orientation on Flow Boiling Process

Effect of Helical Coil Orientation on Flow Boiling Process

Effect of low-cost transcranial magnetic stimulation navigation on hotspot targeting and motor evoked potential variability in the biceps brachii.

Transcranial magnetic stimulation (TMS) can monitor or modulate brain excitability. However, reliability of TMS outcomes depends on consistent coil placement during stimulation. Neuronavigated TMS systems can address this issue, but their cost limits their use outside of specialist research environments. The objective was to evaluate the performance of a low-cost navigated TMS approach in improving coil placement consistency and its effect on motor evoked potentials (MEPs) when targeting the biceps brachii at rest and during voluntary contractions. We implemented a navigated TMS system using a low-cost 3D camera system and open-source software environment programmed using the Unity 3D engine. MEPs were collected from the biceps brachii at rest and during voluntary contractions across two sessions in ten non-disabled individuals. Motor hotspots were recorded and targeted via two conditions: navigated and conventional. The low-cost navigated TMS system reduced coil orientation error (pitch: 1.18°±1.2°, yaw: 1.99°±1.9°, roll: 1.18°±2.2° with navigation, versus pitch: 3.7°±5.7°, yaw: 3.11°±3.1°, roll: 3.8°±9.1° with conventional). The improvement in coil orientation had no effect on MEP amplitudes and variability. The low-cost system is a suitable alternative to expensive systems in tracking the motor hotspot between sessions and quantifying the error in coil placement when delivering TMS. Biceps MEP variability reflects physiological variability across a range of voluntary efforts, that can be captured equally well with navigated or conventional approaches of coil locating.

The impulse noise of TMS inside a 3 T and 9.4 T MRI

Abstract The operation of a transcranial magnetic stimulation (TMS) coil produces high-intensity impulse sounds. In TMS, a magnetic field is generated by a short-duration pulse in the range of thousands of amperes in the coil. When placed in a strong magnetic field, such as inside an magnetic resonance imaging (MRI) bore, the interaction of the magnetic field and the current in the TMS coil can cause strong forces on the coil casing. The strengths of these forces depend on the coil orientation in the main magnetic field (B0). Part of the energy in this process is dissipated in the form of acoustic noise. To conduct concurrent TMS and functional MRI (fMRI) safely, the sound pressure levels (SPLs) generated by the TMS coil must be quantitatively characterized. Measuring the SPLs of fast and loud impulse sounds accurately in the presence of static and gradient magnetic fields is challenging. In this study, we present a method for such measurements and report the SPLs of two commercial MRI-compatible TMS systems inside a 3T MRI scanner and of a prototype multi-channel TMS (mTMS) system inside a 9.4T small-animal MRI scanner. The mTMS coil allows for changing the direction of the electric field (E-field) without physically moving the TMS coil. We measured the acoustic noise generated by the TMS coils with different E-field orientations relative to the B0 field at different stimulation intensities and locations. The measurements were compared to the sound level measured outside the MRI room. SPLs and spectrum of the click sounds changed depending on coil and induced E-field orientation compared to the B0 field. SPLs exceeding the safety limit of 140 dB(C) was measured with all the devices. Our study provide is an important step towards the safety operation of concurrent TMS-fMRI respecting the auditory limits of small animals and humans. Keywords: TMS, mTMS, fMRI, acoustic noise

Adaptive cross approximation for E-field-guided non-invasive magnetic brain stimulation

Abstract Introduction: During transcranial magnetic stimulation (TMS), a coil placed on the scalp driven by a low-frequency pulse is used to modulate brain activity. The TMS induced E-field has been shown to correlate well with stimulated cortical region. As a result, E-field information is essential for the determining where to place the coil and the necessary pulse intensity. A bottleneck to E-field informed TMS is that FEM requires the solution of a large linear systems of equations for each coil placement, making repeated execution of FEM for finding optimum coil placement impractical. Objectives: The goal is to develop a practical tool for E-field dosimetry that allows determination of E-fields in real-time, thereby, enabling the fast computation of optimum coil placement. Methods: We arrange E-field results into a matrix with each column consisting of E-field samples determined from a single coil placement via FEM. Its rows consist of the E-field at a single coil position for all possible coil placements and can be sampled using our previously proposed auxiliary dipole method (ADM). We use the adaptive cross approximation (ACA) to estimate the whole matrix from a few sample columns and rows. Results: This method can evaluate the E-field distribution in a 2 cm diameter ROI from for ∼1000 coil positions and 360 coil orientations with error <2% in under 10 and 20 simulations in a spherical and MRI-derived head model, respectively. For the MRI-derived head model, this method obtained all the fields in <20 minutes. Conclusion: The proposed method enables the fast computation of optimal coil placement and pulse intensity, as well as, it provides E-field distribution inside the ROI for each coil placement.View Large Image Figure ViewerDownload Hi-res image Download (PPT)View Large Image Figure ViewerDownload Hi-res image Download (PPT)View Large Image Figure ViewerDownload Hi-res image Download (PPT)View Large Image Figure ViewerDownload Hi-res image Download (PPT) Keywords: TMS, Low-rank approximation, Coil placement optimizaiton, E-field dosimetry

Electromagnetic Simulation of Signal Distribution of Various RF Endoluminal Loop Geometries with Coil Orientation: Towards a Reconfigurable Design

With the objective of improving MR endoluminal imaging of the colonic wall, electromagnetic simulations of different configurations of single-layer and double-layer, and double-turn endoluminal coil geometries were run. Indeed, during colon navigation, variations in coil orientation with respect to B0 are bound to occur, leading to impaired image acquisition due to a loss of signal uniformity. In this work, three typical coil orientations encountered during navigation were chosen and the resulting signal uniformity of the different geometries was investigated through the simulatedB1x,y/IRtvalues. Sampling this quantity over a circle of radius r enabled us to calculate the coefficient of variation (= standard deviation/mean) for this given distance. This procedure was repeated forr∈5;15 mm, which represents the region of interest in the colon. Our results show that single-loop and double-layer geometries could provide complementary solutions for improved signal uniformity. Finally, using four microelectromechanical system switches, we proposed the design of a reconfigurable endoluminal coil able to switch between those two geometries while also ensuring the active decoupling of the endoluminal coil during the RF transmission of an MR experiment.

Proof of concept study to develop a novel connectivity-based electric-field modelling approach for individualized targeting of transcranial magnetic stimulation treatment

Resting state functional connectivity (rsFC) offers promise for individualizing stimulation targets for transcranial magnetic stimulation (TMS) treatments. However, current targeting approaches do not account for non-focal TMS effects or large-scale connectivity patterns. To overcome these limitations, we propose a novel targeting optimization approach that combines whole-brain rsFC and electric-field (e-field) modelling to identify single-subject, symptom-specific TMS targets. In this proof of concept study, we recruited 91 anxious misery (AM) patients and 25 controls. We measured depression symptoms (MADRS/HAMD) and recorded rsFC. We used a PCA regression to predict symptoms from rsFC and estimate the parameter vector, for input into our e-field augmented model. We modeled 17 left dlPFC and 7 M1 sites using 24 equally spaced coil orientations. We computed single-subject predicted ΔMADRS/HAMD scores for each site/orientation using the e-field augmented model, which comprises a linear combination of the following elementwise products (1) the estimated connectivity/symptom coefficients, (2) a vectorized e-field model for site/orientation, (3) rsFC matrix, scaled by a proportionality constant. In AM patients, our connectivity-based model predicted a significant decrease depression for sites near BA9, but not M1 for coil orientations perpendicular to the cortical gyrus. In control subjects, no site/orientation combination showed a significant predicted change. These results corroborate previous work suggesting the efficacy of left dlPFC stimulation for depression treatment, and predict better outcomes with individualized targeting. They also suggest that our novel connectivity-based e-field modelling approach may effectively identify potential TMS treatment responders and individualize TMS targeting to maximize the therapeutic impact.

Behavioral effects of continuous theta-burst stimulation in macaque parietal cortex

The neural mechanisms underlying the effects of continuous Theta-Burst Stimulation (cTBS) in humans are poorly understood. Animal studies can clarify the effects of cTBS on individual neurons, but behavioral evidence is necessary to demonstrate the validity of the animal model. We investigated the behavioral effect of cTBS applied over parietal cortex in rhesus monkeys performing a visually-guided grasping task with two differently sized objects, which required either a power grip or a pad-to-side grip. We used Fitts’ law, predicting shorter grasping times (GT) for large compared to small objects, to investigate cTBS effects on two different grip types. cTBS induced long-lasting object-specific and dose-dependent changes in GT that remained present for up to two hours. High-intensity cTBS increased GTs for a power grip, but shortened GTs for a pad-to-side grip. Thus, high-intensity stimulation strongly reduced the natural GT difference between objects (i.e. the Fitts’ law effect). In contrast, low-intensity cTBS induced the opposite effects on GT. Modifying the coil orientation from the standard 45-degree to a 30-degree angle induced opposite cTBS effects on GT. These findings represent behavioral evidence for the validity of the nonhuman primate model to study the neural underpinnings of non-invasive brain stimulation.

Dosimetry Analysis in Non-brain Tissues During TMS Exposure of Broca's and M1 Areas.

For human protection, the internal electric field is used as a dosimetric quantity for electromagnetic fields lower than 5–10 MHz. According to international standards, in this frequency range, electrostimulation is the main adverse effect against which protection is needed. One of the topics to be investigated is the quantification of the internal electric field threshold levels of perception and pain. Pain has been reported as a side effect during transcranial magnetic stimulation (TMS), especially during stimulation of the Broca’s (speech) area of the brain. In this study, we designed an experiment to conduct a dosimetry analysis to quantify the internal electric field corresponding to perception and pain thresholds when targeting the Broca’s and M1 areas from magnetic stimulator exposure. Dosimetry analysis was conducted using a multi-scale analysis in an individualized head model to investigate electrostimulation in an axonal model. The main finding is that the stimulation on the primary motor cortex has higher perception and pain thresholds when compared to Broca’s area. Also, TMS-induced electric field applied to Broca’s area exhibited dependence on the coil orientation at lower electric field threshold which was found to be related to the location and thickness of pain fibers. The derived dosimetry quantities provide a scientific rationale for the development of human protection guidelines and the estimation of possible side effects of magnetic stimulation in clinical applications.

Joint Design of Communication, Wireless Energy Transfer, and Control for Swarm Autonomous Underwater Vehicles

A swarm of Autonomous Underwater Vehicles (AUVs) can provide richer spatial-temporal information than the traditional single-robot system, which can be used for underwater mapping, exploration, target tracking, among others. However, the limitation of AUVs’ battery cannot support persistent services, which restricts AUVs’ operating range and mission duration. In this paper, a mobile underwater charging solution is developed that can continuously recharge a swarm of AUVs by using a wireless mobile charger. Magnetic induction-based communication and wireless energy transfer are employed. This paper first shows that by using tri-axis coils, reliable wireless communication and wireless energy transfer without coil orientation losses can be obtained. After that, wireless communication, motion control, and wireless energy transfer are jointly designed for a swarm of mission-driven AUVs. In particular, optimal continuous motion controllers are developed for AUVs to avoid intra-swarm collisions and networking protocols are designed to optimally allocate resources for wireless communication and wireless energy transfer. The proposed approach can guide AUVs to their destinations, while maintaining wireless network integrity and maximizing wireless energy transfer efficiency, upon which the constraints on AUVs’ batteries can be eliminated and cheaper and smaller AUVs can be employed for various underwater applications.

Effect of coil positioning and orientation of the quadruple butterfly coil during transcranial magnetic stimulation

Transcranial Magnetic Stimulation (TMS) is a non-invasive neuromodulation technique for treating neurological and psychiatric disorders. It is a proven technique that is safe and considered very effective when compared to conventional brain surgery or drug therapy. Researchers and clinicians are interested in understanding the distribution of the induced electric field (E-Field) during TMS and determining its effectiveness in treating neurological disorders. TMS studies are primarily focused on enhancing the focality and depth of penetration of the induced electric field in order to increase its effectiveness. Coil orientation has been confirmed to have an effect on the magnitude and direction of the induced E-Field. In this paper, we study the effect of the orientation of the novel Quadruple Butterfly Coil (QBC) on the distribution of the induced E-Field. Finite element analyses were conducted with the orientation of the QBC in steps of 15° over the vertex of two head models and about the transverse (XY –) plane and coronal (XZ –) plane of the head model. The maximum electric field intensity (E-Max) and stimulated volume of the brain (V-Half) were computed and compared to determine the optimal coil orientation.

Coil orientation affects pain sensation during single-pulse transcranial magnetic stimulation over Broca’s area

ObjectivePain sensation at the site of stimulation is a side effect of transcranial magnetic stimulation (TMS). The purpose of this study was to investigate how or whether the coil orientation affected TMS-induced pain on Broca’s area (BA) or primary motor cortex (M1). MethodsIn Experiment 1, we measured pain thresholds during single-pulse TMS delivered over BA or left M1 at seven coil orientation angles (−90° to 90°, in 30° increments) relative to the posterior-anterior (PA) orientation. In Experiment 2, we evaluated subjective pain intensity when delivering TMS at an intensity of 110% of the resting motor threshold, which is commonly used in conventional TMS studies. ResultsIn Experiment 1, we found a significant relationship between coil orientation and pain thresholds during BA stimulation but not M1 stimulation. During BA stimulation, pain thresholds were significantly lower when the coil orientation was 30° upward (−30° condition) relative to the PA orientation compared with 60° downward (60° condition). In Experiment 2, pain sensations were significantly stronger in the −30° condition compared with those in the 60° condition. We also confirmed that the averaged location of pain on the head in both conditions were more than 25 mm from the left lateral orbital rim. ConclusionsThe coil orientation of TMS over BA affects pain sensations. This might be attributable to the activation of nociceptors and nociceptive fibers in the muscle tissues above BA, rather than the orbicularis oculi muscle. SignificanceAlthough the influence of coil orientation on the TMS efficacy is unclear, this study suggests that manipulating the orientation of the TMS coil may be helpful in reducing pain when applying TMS to BA.

Comparative Analysis of Coil Structures and Orientations of Single Transmitter and Multi Receivers Wireless Power Transfer System

Single transmitter and multi receiver (STMR) based WPT system is used to power multiple loads at a time. It consists of some limitations like long distance power transfer, mutual inductance between receiver coils and misalignment of receiver coils. this paper is going to give a detailed information about different designs of STMR, which are going to overcome the limitations of STMR. Different designs proposed by different authors are wireless power repeater system with single coil in each repeater, wireless power repeater system with two coils in each repeater, spherical strongly coupled magnetic resonant, square shape coils, maglev train IPT system and cube shaped unidirectional flux transmitter type. The above-mentioned designs are analysed and concluded a best design from it, depending up on applications and discussed about the control systems used in STMR.

Fast computational optimization of TMS coil placement for individualized electric field targeting

BackgroundDuring transcranial magnetic stimulation (TMS) a coil placed on the scalp is used to non-invasively modulate activity of targeted brain networks via a magnetically induced electric field (E-field). Ideally, the E-field induced during TMS is concentrated on a targeted cortical region of interest (ROI). Determination of the coil position and orientation that best achieve this objective presently requires a large computational effort. ObjectiveTo improve the accuracy of TMS we have developed a fast computational auxiliary dipole method (ADM) for determining the optimum coil position and orientation. The optimum coil placement maximizes the E-field along a predetermined direction or, alternatively, the overall E-field magnitude in the targeted ROI. Furthermore, ADM can assess E-field uncertainty resulting from precision limitations of TMS coil placement protocols. MethodADM leverages the electromagnetic reciprocity principle to compute rapidly the TMS induced E-field in the ROI by using the E-field generated by a virtual constant current source residing in the ROI. The framework starts by solving for the conduction currents resulting from this ROI current source. Then, it rapidly determines the average E-field induced in the ROI for each coil position by using the conduction currents and a fast-multipole method. To further speed-up the computations, the coil is approximated using auxiliary dipoles enabling it to represent all coil orientations for a given coil position with less than 600 dipoles. ResultsUsing ADM, the E-fields generated in an MRI-derived head model when the coil is placed at 5900 different scalp positions and 360 coil orientations per position (over 2.1 million unique configurations) can be determined in under 15 min on a standard laptop computer. This enables rapid extraction of the optimum coil position and orientation as well as the E-field variation resulting from coil positioning uncertainty. ADM is implemented in SimNIBS 3.2. ConclusionADM enables the rapid determination of coil placement that maximizes E-field delivery to a specific brain target. This method can find the optimum coil placement in under 15 min enabling its routine use for TMS. Furthermore, it enables the fast quantification of uncertainty in the induced E-field due to limited precision of TMS coil placement protocols, enabling minimization and statistical analysis of the E-field dose variability.