How the brain tissue shapes the electric field induced by transcranial magnetic stimulation

The electric field distribution in the brain during TTFields therapy and its dependence on tissue dielectric properties and anatomy: a computational study

Tumor treating fields (TTFields) are a non-invasive, anti-mitotic and approved treatment for recurrent glioblastoma multiforme (GBM) patients. In vitro studies have shown that inhibition of cell division in glioma is achieved when the applied alternating electric field has a frequency in the range of 200 kHz and an amplitude of 1-3 V cm(-1). Our aim is to calculate the electric field distribution in the brain during TTFields therapy and to investigate the dependence of these predictions on the heterogeneous, anisotropic dielectric properties used in the computational model. A realistic head model was developed by segmenting MR images and by incorporating anisotropic conductivity values for the brain tissues. The finite element method (FEM) was used to solve for the electric potential within a volume mesh that consisted of the head tissues, a virtual lesion with an active tumour shell surrounding a necrotic core, and the transducer arrays. The induced electric field distribution is highly non-uniform. Average field strength values are slightly higher in the tumour when incorporating anisotropy, by about 10% or less. A sensitivity analysis with respect to the conductivity and permittivity of head tissues shows a variation in field strength of less than 42% in brain parenchyma and in the tumour, for values within the ranges reported in the literature. Comparing results to a previously developed head model suggests significant inter-subject variability. This modelling study predicts that during treatment with TTFields the electric field in the tumour exceeds 1 V cm(-1), independent of modelling assumptions. In the future, computational models may be useful to optimize delivery of TTFields.

Functional neuronal anisotropy assessed with neuronavigated transcranial magnetic stimulation

BACKGROUND

Transcranial magnetic stimulation (TMS) can evaluate cortical excitability and integrity of motor pathways via TMS-induced responses. The responses are affected by the orientation of the stimulated neurons with respect to the direction of the TMS-induced electric field. Therefore, besides being a functional imaging tool, TMS may potentially assess the local structural properties. Yet, TMS has not been used for this purpose.

NEW METHOD

A novel principle to evaluate the relation between function and structure of the motor cortex is presented. This functional anisotropy is evaluated by an anisotropy index (AI), based on motor evoked potential amplitudes induced with different TMS coil orientations, i.e. different electric field directions at a cortical target. To compare the AI with anatomical anisotropy in an explorative manner, diffusion tensor imaging-derived fractional anisotropy (FA) was estimated at different depths near the stimulation site.

RESULTS

AI correlated inversely with cortical excitability through the TMS-induced electric field at motor threshold level. Further, there was a trend of negative correlation between AI and FA.

COMPARISON WITH EXISTING METHODS

None of the existing methods alone can detect the relationship between direct motor cortex activation and local neuronal structure.

CONCLUSIONS

The AI appears to provide information on the functional neuronal anisotropy of the motor cortex by coupling neurophysiology and neuroanatomy within the stimulated cortical region. The AI could prove useful in the evaluation of neurological disorders and traumas involving concurrent structural and functional changes in the motor cortex. Further studies on patients are needed to confirm the usability of AI.

Neuron matters: electric activation of neuronal tissue is dependent on the interaction between the neuron and the electric field

In laboratory research and clinical practice, externally-applied electric fields have been widely used to control neuronal activity. It is generally accepted that neuronal excitability is controlled by electric current that depolarizes or hyperpolarizes the excitable cell membrane. What determines the amount of polarization? Research on the mechanisms of electric stimulation focus on the optimal control of the field properties (frequency, amplitude, and direction of the electric currents) to improve stimulation outcomes. Emerging evidence from modeling and experimental studies support the existence of interactions between the targeted neurons and the externally-applied electric fields. With cell-field interaction, we suggest a two-way process. When a neuron is positioned inside an electric field, the electric field will induce a change in the resting membrane potential by superimposing an electrically-induced transmembrane potential (ITP). At the same time, the electric field can be perturbed and re-distributed by the cell. This cell-field interaction may play a significant role in the overall effects of stimulation. The redistributed field can cause secondary effects to neighboring cells by altering their geometrical pattern and amount of membrane polarization. Neurons excited by the externally-applied electric field can also affect neighboring cells by ephaptic interaction. Both aspects of the cell-field interaction depend on the biophysical properties of the neuronal tissue, including geometric (i.e., size, shape, orientation to the field) and electric (i.e., conductivity and dielectricity) attributes of the cells. The biophysical basis of the cell-field interaction can be explained by the electromagnetism theory. Further experimental and simulation studies on electric stimulation of neuronal tissue should consider the prospect of a cell-field interaction, and a better understanding of tissue inhomogeneity and anisotropy is needed to fully appreciate the neural basis of cell-field interaction as well as the biological effects of electric stimulation.

Validation of Computational Studies for Electrical Brain Stimulation With Phantom Head Experiments

BACKGROUND

Although computational studies of electrical brain stimulation (EBS) have received attention as a cost-effective tool, few studies have validated the technique, particularly in invasive cortical stimulation.

OBJECTIVE

In order to validate such studies, we used EBS to compare electric potential distributions generated by both numerical simulations and empirical measurements in three phantom head models (one-/three-layered spherical heads and MRI-based head).

METHODS

We constructed spherical phantom heads that consisted of one or three layers, and an anatomical, MRI-based phantom that consisted of three layers and represented the brain or brain/skull/scalp in order to perform both numerical simulations using the finite element method (FEM) and experimental measurements. Two stimulation electrodes (cathode and anode) were implanted in the phantoms to inject regulated input voltage, and the electric potential distributions induced were measured at various points located either on the surface or deep within the phantoms.

RESULTS

We observed that both the electric potential distributions from the numerical simulations and experiments behaved similarly and resulted in average relative differences of 5.4% (spherical phantom) and 10.3% (MRI-based phantom).

CONCLUSIONS

This study demonstrated that numerical simulation is reasonably consistent with actual experimental measurements; thus, because of its cost-effectiveness, EBS computational studies may be an attractive approach for necessary intensive/extensive studies.

Computational Study of Subdural Cortical Stimulation: Effects of Simulating Anisotropic Conductivity on Activation of Cortical Neurons

Subdural cortical stimulation (SuCS) is an appealing method in the treatment of neurological disorders, and computational modeling studies of SuCS have been applied to determine the optimal design for electrotherapy. To achieve a better understanding of computational modeling on the stimulation effects of SuCS, the influence of anisotropic white matter conductivity on the activation of cortical neurons was investigated in a realistic head model. In this paper, we constructed pyramidal neuronal models (layers 3 and 5) that showed primary excitation of the corticospinal tract, and an anatomically realistic head model reflecting complex brain geometry. The anisotropic information was acquired from diffusion tensor magnetic resonance imaging (DT-MRI) and then applied to the white matter at various ratios of anisotropic conductivity. First, we compared the isotropic and anisotropic models; compared to the isotropic model, the anisotropic model showed that neurons were activated in the deeper bank during cathodal stimulation and in the wider crown during anodal stimulation. Second, several popular anisotropic principles were adapted to investigate the effects of variations in anisotropic information. We observed that excitation thresholds varied with anisotropic principles, especially with anodal stimulation. Overall, incorporating anisotropic conductivity into the anatomically realistic head model is critical for accurate estimation of neuronal responses; however, caution should be used in the selection of anisotropic information.

Computational and experimental analysis of TMS-induced electric field vectors critical to neuronal activation

OBJECTIVE

Transcranial magnetic stimulation (TMS) represents a powerful technique to noninvasively modulate cortical neurophysiology in the brain. However, the relationship between the magnetic fields created by TMS coils and neuronal activation in the cortex is still not well-understood, making predictable cortical activation by TMS difficult to achieve. Our goal in this study was to investigate the relationship between induced electric fields and cortical activation measured by blood flow response. Particularly, we sought to discover the E-field characteristics that lead to cortical activation.

APPROACH

Subject-specific finite element models (FEMs) of the head and brain were constructed for each of six subjects using magnetic resonance image scans. Positron emission tomography (PET) measured each subject's cortical response to image-guided robotically-positioned TMS to the primary motor cortex. FEM models that employed the given coil position, orientation, and stimulus intensity in experimental applications of TMS were used to calculate the electric field (E-field) vectors within a region of interest for each subject. TMS-induced E-fields were analyzed to better understand what vector components led to regional cerebral blood flow (CBF) responses recorded by PET.

MAIN RESULTS

This study found that decomposing the E-field into orthogonal vector components based on the cortical surface geometry (and hence, cortical neuron directions) led to significant differences between the regions of cortex that were active and nonactive. Specifically, active regions had significantly higher E-field components in the normal inward direction (i.e., parallel to pyramidal neurons in the dendrite-to-axon orientation) and in the tangential direction (i.e., parallel to interneurons) at high gradient. In contrast, nonactive regions had higher E-field vectors in the outward normal direction suggesting inhibitory responses.

SIGNIFICANCE

These results provide critical new understanding of the factors by which TMS induces cortical activation necessary for predictive and repeatable use of this noninvasive stimulation modality.

A setup for administering TMS to medial and lateral cortical areas during whole-brain FMRI recording

SUMMARY

Stimulating brain areas with transcranial magnetic stimulation (TMS) while concurrently and noninvasively recording brain activity changes through functional MRI enables a new range of investigations about causal interregional interactions in the human brain. However, standard head-coil arrangements for current methods for concurrent TMS-functional MRI somewhat restrict the cortical brain regions that can be targeted with TMS because space in typical MR head coils is limited. Another limitation for concurrent TMS-functional MRI approaches concerns the estimation of the precise stimulation site, which can limit the interpretation of the activity changes induced by TMS and increase the variability of the stimulation effects. Here, we present a novel approach using flexible MR receiver coils, allowing for stimulation of a large part of the cortex including more lateral areas. Furthermore, we present a fast and economical method to determine the precise location of the stimulation coil during scanning. This point-based registration method can accurately compute, during scanning, where TMS pulses are delivered. We validated this approach by stimulating medial (M1) and more lateral (dorsal part of the supramarginal gyrus) brain areas concurrently with functional MRI. Activation close to but not directly at the stimulated location and in distal areas connected to the targeted site was observed. This study provides a proof of concept that TMS of medial and lateral brain areas is feasible without significantly compromising brain coverage and that one can precisely determine the exact coil location inside the bore to verify targeting of brain areas.

The coil orientation dependency of the electric field induced by TMS for M1 and other brain areas

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.

Electronic supplementary material

The online version of this article (doi:10.1186/s12984-015-0036-2) contains supplementary material, which is available to authorized users.

Subject-Specific Multiscale Modeling to Investigate Effects of Transcranial Magnetic Stimulation

OBJECTIVE

Transcranial magnetic stimulation (TMS) is an effective intervention in noninvasive neuromodulation used to treat a number of neurophysiological disorders. Predicting the spatial extent to which neural tissue is affected by TMS remains a challenge. The goal of this study was to develop a computational model to predict specific locations of neural tissue that are activated during TMS. Using this approach, we assessed the effects of changing TMS coil orientation and waveform.

MATERIALS AND METHODS

We integrated novel techniques to develop a subject-specific computational model, which contains three main components: 1) a figure-8 coil (Magstim, Magstim Company Limited, Carmarthenshire, UK); 2) an electromagnetic, time-dependent, nonhomogeneous, finite element model of the whole head; and 3) an adaptation of a previously published pyramidal cell neuron model. We then used our modeling approach to quantify the spatial extent of affected neural tissue for changes in TMS coil rotation and waveform.

RESULTS

We found that our model shows more detailed predictions than previously published models, which underestimate the spatial extent of neural activation. Our results suggest that fortuitous sites of neural activation occur for all tested coil orientations. Additionally, our model predictions show that excitability of individual neural elements changes with a coil rotation of ±15°.

CONCLUSIONS

Our results indicate that the extent of neuromodulation is more widespread than previous published models suggest. Additionally, both specific locations in cortex and the extent of stimulation in cortex depend on coil orientation to within ±15° at a minimum. Lastly, through computational means, we are able to provide insight into the effects of TMS at a cellular level, which is currently unachievable by imaging modalities.

Projecting Navigated TMS Sites on the Gyral Anatomy Decreases Inter-subject Variability of Cortical Motor Maps

BACKGROUND

Magnetic resonance images are being increasingly deployed in conjunction with navigated transcranial magnetic stimulation (nTMS) to account for inter-individual differences in brain anatomy as well as to reduce the variability of mapping findings.

OBJECTIVE

However, despite the fact that the individual gyral anatomy has a significant impact on the TMS-induced electrical field distributions, these approaches still project the TMS coil positions as a plane grid of target points on the brain surface and fail to account for differences in cortex morphology.

METHODS

In this study, we have introduced a technique for projecting nTMS sites onto the gyral anatomy to decrease the variability of cortical motor maps between subjects in normalized space. This involved interpolating the discrete map points in the normalized volume space and performing additional surface coregistration.

RESULTS

By applying this technique, we increased the spatial overlap between the cortical maps of the extensor digitorum communis muscle between subjects from 80% to 100%. We also managed to significantly reduce the mean Euclidean distance between the average center of gravity and the average hotspots to the respective individual spots from 8 mm to 6.5 mm.

CONCLUSION

Our approach facilitates the study of the functional topography of distinct behavioral properties with high spatial resolution, thereby constituting a valuable tool for precise group analysis of cortical TMS maps.

Determinants of the electric field during transcranial direct current stimulation

Transcranial direct current stimulation (tDCS) causes a complex spatial distribution of the electric current flow in the head which hampers the accurate localization of the stimulated brain areas. In this study we show how various anatomical features systematically shape the electric field distribution in the brain during tDCS. We constructed anatomically realistic finite element (FEM) models of two individual heads including conductivity anisotropy and different skull layers. We simulated a widely employed electrode montage to induce motor cortex plasticity and moved the stimulating electrode over the motor cortex in small steps to examine the resulting changes of the electric field distribution in the underlying cortex. We examined the effect of skull thickness and composition on the passing currents showing that thinner skull regions lead to higher electric field strengths. This effect is counteracted by a larger proportion of higher conducting spongy bone in thicker regions leading to a more homogenous current over the skull. Using a multiple regression model we could identify key factors that determine the field distribution to a significant extent, namely the thicknesses of the cerebrospinal fluid and the skull, the gyral depth and the distance to the anode and cathode. These factors account for up to 50% of the spatial variation of the electric field strength. Further, we demonstrate that individual anatomical factors can lead to stimulation "hotspots" which are partly resistant to electrode positioning. Our results give valuable novel insights in the biophysical foundation of tDCS and highlight the importance to account for individual anatomical factors when choosing an electrode montage.

Is sham cTBS real cTBS? The effect on EEG dynamics

Increasing sensitivity of modern evaluation tools allows for the study of weaker electric stimulation effects on neural populations. In the current study we examined the effects of sham continuous theta burst (cTBS) transcranial magnetic stimulation to the left dorsolateral prefrontal cortex (DLPFC) upon somatosensory evoked potentials (SEP) and frontal-parietal phase coupling of alpha and beta bands. Sham TMS results in an induced electric field amplitude roughly 5% that of real TMS with a similar spatial extent in cortex. Both real and sham cTBS reduced the amplitude of the frontal P14-N30 SEP and increased local phase coupling in the alpha-beta frequency bands of left frontal cortex. In addition, both sham and real cTBS increased frontal-parietal phase coupling in the alpha-beta bands concomitant with an increase in amplitude of parietal P50-N70 complex. These data suggest that weak electric fields from sham cTBS can affect both local and downstream neuronal circuits, though in a different manner than high strength TMS.

FDTD-based Transcranial Magnetic Stimulation model applied to specific neurodegenerative disorders

Non-invasive treatment of neurodegenerative diseases is particularly challenging in Western countries, where the population age is increasing. In this work, magnetic propagation in human head is modelled by Finite-Difference Time-Domain (FDTD) method, taking into account specific characteristics of Transcranial Magnetic Stimulation (TMS) in neurodegenerative diseases. It uses a realistic high-resolution three-dimensional human head mesh. The numerical method is applied to the analysis of magnetic radiation distribution in the brain using two realistic magnetic source models: a circular coil and a figure-8 coil commonly employed in TMS. The complete model was applied to the study of magnetic stimulation in Alzheimer and Parkinson Diseases (AD, PD). The results show the electrical field distribution when magnetic stimulation is supplied to those brain areas of specific interest for each particular disease. Thereby the current approach entails a high potential for the establishment of the current underdeveloped TMS dosimetry in its emerging application to AD and PD.

Modeling TMS-induced I-waves in human motor cortex

Despite many years of research, it is still unknown how exactly transcranial magnetic stimulation activates cortical circuits. A recent computational model by Rusu et al. (2014) has attempted to shed light on potential underlying mechanisms and has successfully explained key experimental findings on I-wave physiology. Here, we critically discuss this model, point out some of its shortcomings, and suggest a number of extensions that may be necessary for it to capture additional existing and emerging data on the physiology of I-waves.

Effective electric fields along realistic DTI-based neural trajectories for modelling the stimulation mechanisms of TMS

In transcranial magnetic stimulation (TMS), an applied alternating magnetic field induces an electric field in the brain that can interact with the neural system. It is generally assumed that this induced electric field is the crucial effect exciting a certain region of the brain. More specifically, it is the component of this field parallel to the neuron's local orientation, the so-called effective electric field, that can initiate neuronal stimulation. Deeper insights on the stimulation mechanisms can be acquired through extensive TMS modelling. Most models study simple representations of neurons with assumed geometries, whereas we embed realistic neural trajectories computed using tractography based on diffusion tensor images. This way of modelling ensures a more accurate spatial distribution of the effective electric field that is in addition patient and case specific. The case study of this paper focuses on the single pulse stimulation of the left primary motor cortex with a standard figure-of-eight coil. Including realistic neural geometry in the model demonstrates the strong and localized variations of the effective electric field between the tracts themselves and along them due to the interplay of factors such as the tract's position and orientation in relation to the TMS coil, the neural trajectory and its course along the white and grey matter interface. Furthermore, the influence of changes in the coil orientation is studied. Investigating the impact of tissue anisotropy confirms that its contribution is not negligible. Moreover, assuming isotropic tissues lead to errors of the same size as rotating or tilting the coil with 10 degrees. In contrast, the model proves to be less sensitive towards the not well-known tissue conductivity values.

Transcranial direct current stimulation over the left prefrontal cortex increases randomness of choice in instrumental learning

INTRODUCTION

There is growing evidence from neuro-computational studies that instrumental learning involves the dynamic interaction of a computationally rigid, low-level striatal and a more flexible, high-level prefrontal component.

METHODS

To evaluate the role of the prefrontal cortex in instrumental learning, we applied anodal transcranial direct current stimulation (tDCS) optimized for the left dorsolateral prefrontal cortex, by using realistic MR-derived finite element model-based electric field simulations. In a study with a double-blind, sham-controlled, repeated-measures design, sixteen male participants performed a probabilistic learning task while receiving anodal and sham tDCS in a counterbalanced order.

RESULTS

Compared to sham tDCS, anodal tDCS significantly increased the amount of maladaptive shifting behavior after optimal outcomes during learning when reward probabilities were highly dissociable. Derived parameters of the Q-learning computational model further revealed a significantly increased model parameter that was sensitive to random action selection in the anodal compared to the sham tDCS session, whereas the learning rate parameter was not influenced significantly by tDCS.

CONCLUSION

These results congruently indicate that prefrontal tDCS during instrumental learning increased randomness of choice, possibly reflecting the influence of the cognitive prefrontal component.

Influence of different geometric representations of the volume conductor on nerve activation during electrical stimulation

Volume conductor models with different geometric representations, such as the parallel layer model (PM), the cylindrical layer model (CM), or the anatomically based model (AM), have been employed during the implementation of bioelectrical models for electrical stimulation (FES). Evaluating their strengths and limitations to predict nerve activation is fundamental to achieve a good trade-off between accuracy and computation time. However, there are no studies aimed at clarifying the following questions. (1) Does the nerve activation differ between CM and PM? (2) How well do CM and PM approximate an AM? (3) What is the effect of the presence of blood vessels and nerve trunk on nerve activation prediction? Therefore, in this study, we addressed these questions by comparing nerve activation between CM, PM, and AM models by FES. The activation threshold was used to evaluate the models under different configurations of superficial electrodes (size and distance), nerve depths, and stimulation sites. Additionally, the influences of the sciatic nerve, femoral artery, and femoral vein were inspected for a human thigh. The results showed that the CM and PM had a high error rate, but the variation of the activation threshold followed the same tendency for electrode size and interelectrode distance variation as AM.

Validating computationally predicted TMS stimulation areas using direct electrical stimulation in patients with brain tumors near precentral regions

The spatial extent of transcranial magnetic stimulation (TMS) is of paramount interest for all studies employing this method. It is generally assumed that the induced electric field is the crucial parameter to determine which cortical regions are excited. While it is difficult to directly measure the electric field, one usually relies on computational models to estimate the electric field distribution. Direct electrical stimulation (DES) is a local brain stimulation method generally considered the gold standard to map structure-function relationships in the brain. Its application is typically limited to patients undergoing brain surgery. In this study we compare the computationally predicted stimulation area in TMS with the DES area in six patients with tumors near precentral regions. We combine a motor evoked potential (MEP) mapping experiment for both TMS and DES with realistic individual finite element method (FEM) simulations of the electric field distribution during TMS and DES. On average, stimulation areas in TMS and DES show an overlap of up to 80%, thus validating our computational physiology approach to estimate TMS excitation volumes. Our results can help in understanding the spatial spread of TMS effects and in optimizing stimulation protocols to more specifically target certain cortical regions based on computational modeling.

Simulating transcranial direct current stimulation with a detailed anisotropic human head model

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.

Transcranial focused ultrasound modulates the activity of primary somatosensory cortex in humans

Improved methods of noninvasively modulating human brain function are needed. Here we probed the influence of transcranial focused ultrasound (tFUS) targeted to the human primary somatosensory cortex (S1) on sensory-evoked brain activity and sensory discrimination abilities. The lateral and axial spatial resolution of the tFUS beam implemented were 4.9 mm and 18 mm, respectively. Electroencephalographic recordings showed that tFUS significantly attenuated the amplitudes of somatosensory evoked potentials elicited by median nerve stimulation. We also found that tFUS significantly modulated the spectral content of sensory-evoked brain oscillations. The changes produced by tFUS on sensory-evoked brain activity were abolished when the acoustic beam was focused 1 cm anterior or posterior to S1. Behavioral investigations showed that tFUS targeted to S1 enhanced performance on sensory discrimination tasks without affecting task attention or response bias. We conclude that tFUS can be used to focally modulate human cortical function.

Coil design considerations for deep transcranial magnetic stimulation

OBJECTIVES

To explore the field characteristics and design tradeoffs of coils for deep transcranial magnetic stimulation (dTMS).

METHODS

We simulated parametrically two dTMS coil designs on a spherical head model using the finite element method, and compare them with five commercial TMS coils, including two that are FDA approved for the treatment of depression (ferromagnetic-core figure-8 and H1 coil).

RESULTS

Smaller coils have a focality advantage over larger coils; however, this advantage diminishes with increasing target depth. Smaller coils have the disadvantage of producing stronger field in the superficial cortex and requiring more energy. When the coil dimensions are large relative to the head size, the electric field decay in depth becomes linear, indicating that, at best, the electric field attenuation is directly proportional to the depth of the target. Ferromagnetic cores improve electrical efficiency for targeting superficial brain areas; however magnetic saturation reduces the effectiveness of the core for deeper targets, especially for highly focal coils. Distancing winding segments from the head, as in the H1 coil, increases the required stimulation energy.

CONCLUSIONS

Among standard commercial coils, the double cone coil offers high energy efficiency and balance between stimulated volume and superficial field strength. Direct TMS of targets at depths of ~4 cm or more results in superficial stimulation strength that exceeds the upper limit in current rTMS safety guidelines. Approaching depths of ~6 cm is almost certainly unsafe considering the excessive superficial stimulation strength and activated brain volume.

SIGNIFICANCE

Coil design limitations and tradeoffs are important for rational and safe exploration of dTMS.

Unraveling the cellular and molecular mechanisms of repetitive magnetic stimulation

Despite numerous clinical studies, which have investigated the therapeutic potential of repetitive transcranial magnetic stimulation (rTMS) in various brain diseases, our knowledge of the cellular and molecular mechanisms underlying rTMS-based therapies remains limited. Thus, a deeper understanding of rTMS-induced neural plasticity is required to optimize current treatment protocols. Studies in small animals or appropriate in vitro preparations (including models of brain diseases) provide highly useful experimental approaches in this context. State-of-the-art electrophysiological and live-cell imaging techniques that are well established in basic neuroscience can help answering some of the major questions in the field, such as (i) which neural structures are activated during TMS, (ii) how does rTMS induce Hebbian plasticity, and (iii) are other forms of plasticity (e.g., metaplasticity, structural plasticity) induced by rTMS? We argue that data gained from these studies will support the development of more effective and specific applications of rTMS in clinical practice.

Controlling stimulation strength and focality in electroconvulsive therapy via current amplitude and electrode size and spacing: comparison with magnetic seizure therapy

OBJECTIVES

Understanding the relationship between the stimulus parameters of electroconvulsive therapy (ECT) and the electric field characteristics could guide studies on improving risk/benefit ratio. We aimed to determine the effect of current amplitude and electrode size and spacing on the ECT electric field characteristics, compare ECT focality with magnetic seizure therapy (MST), and evaluate stimulus individualization by current amplitude adjustment.

METHODS

Electroconvulsive therapy and double-cone-coil MST electric field was simulated in a 5-shell spherical human head model. A range of ECT electrode diameters (2-5 cm), spacing (1-25 cm), and current amplitudes (0-900 mA) was explored. The head model parameters were varied to examine the stimulus current adjustment required to compensate for interindividual anatomical differences.

RESULTS

By reducing the electrode size, spacing, and current, the ECT electric field can be more focal and superficial without increasing scalp current density. By appropriately adjusting the electrode configuration and current, the ECT electric field characteristics can be made to approximate those of MST within 15%. Most electric field characteristics in ECT are more sensitive to head anatomy variation than in MST, especially for close electrode spacing. Nevertheless, ECT current amplitude adjustment of less than 70% can compensate for interindividual anatomical variability.

CONCLUSIONS

The strength and focality of ECT can be varied over a wide range by adjusting the electrode size, spacing, and current. If desirable, ECT can be made as focal as MST while using simpler stimulation equipment. Current amplitude individualization can compensate for interindividual anatomical variability.

PET-based confirmation of orientation sensitivity of TMS-induced cortical activation in humans

BACKGROUND

Currently, it is difficult to predict precise regions of cortical activation in response to transcranial magnetic stimulation (TMS). Most analytical approaches focus on applied magnetic field strength in the target region as the primary factor, placing activation on the gyral crowns. However, imaging studies support M1 targets being typically located in the sulcal banks.

OBJECTIVE/HYPOTHESIS

To more thoroughly investigate this inconsistency, we sought to determine whether neocortical surface orientation was a critical determinant of regional activation.

METHODS

MR images were used to construct cortical and scalp surfaces for 18 subjects. The angle (θ) between the cortical surface normal and its nearest scalp normal for ~50,000 cortical points per subject was used to quantify cortical location (i.e., gyral vs. sulcal). TMS-induced activations of primary motor cortex (M1) were compared to brain activations recorded during a finger-tapping task using concurrent positron emission tomographic (PET) imaging.

RESULTS

Brain activations were primarily sulcal for both the TMS and task activations (P < 0.001 for both) compared to the overall cortical surface orientation. Also, the location of maximal blood flow in response to either TMS or finger-tapping correlated well using the cortical surface orientation angle or distance to scalp (P < 0.001 for both) as criteria for comparison between different neocortical activation modalities.

CONCLUSION

This study provides further evidence that a major factor in cortical activation using TMS is the orientation of the cortical surface with respect to the induced electric field. The results show that, despite the gyral crown of the cortex being subjected to a larger magnetic field magnitude, the sulcal bank of M1 had larger cerebral blood flow (CBF) responses during TMS.

Targeting of white matter tracts with transcranial magnetic stimulation

BACKGROUND

TMS activations of white matter depend not only on the distance from the coil, but also on the orientation of the axons relative to the TMS-induced electric field, and especially on axonal bends that create strong local field gradient maxima. Therefore, tractography contains potentially useful information for TMS targeting.

OBJECTIVE/METHODS

Here, we utilized 1-mm resolution diffusion and structural T1-weighted MRI to construct large-scale tractography models, and localized TMS white matter activations in motor cortex using electromagnetic forward modeling in a boundary element model (BEM).

RESULTS

As expected, in sulcal walls, pyramidal cell axonal bends created preferred sites of activation that were not found in gyral crowns. The model agreed with the well-known coil orientation sensitivity of motor cortex, and also suggested unexpected activation distributions emerging from the E-field and tract configurations. We further propose a novel method for computing the optimal coil location and orientation to maximally stimulate a pre-determined axonal bundle.

CONCLUSIONS

Diffusion MRI tractography with electromagnetic modeling may improve spatial specificity and efficacy of TMS.

A key region in the human parietal cortex for processing proprioceptive hand feedback during reaching movements

Seemingly effortless, we adjust our movements to continuously changing environments. After initiation of a goal-directed movement, the motor command is under constant control of sensory feedback loops. The main sensory signals contributing to movement control are vision and proprioception. Recent neuroimaging studies have focused mainly on identifying the parts of the posterior parietal cortex (PPC) that contribute to visually guided movements. We used event-related TMS and force perturbations of the reaching hand to test whether the same sub-regions of the left PPC contribute to the processing of proprioceptive-only and of multi-sensory information about hand position when reaching for a visual target. TMS over two distinct stimulation sites elicited differential effects: TMS applied over the posterior part of the medial intraparietal sulcus (mIPS) compromised reaching accuracy when proprioception was the only sensory information available for correcting the reaching error. When visual feedback of the hand was available, TMS over the anterior intraparietal sulcus (aIPS) prolonged reaching time. Our results show for the first time the causal involvement of the posterior mIPS in processing proprioceptive feedback for online reaching control, and demonstrate that distinct cortical areas process proprioceptive-only and multi-sensory information for fast feedback corrections.

Quantifying uncertainty in Transcranial Magnetic Stimulation - A high resolution simulation study in ICBM space

Transcranial Magnetic Stimulation offers enormous potential for noninvasive brain stimulation. While it is known that brain tissue significantly "reshapes" induced field and charge distributions, most modeling investigations to-date have focused on single-subject data with limited generality. Further, the effects of the significant uncertainties which exist in the simulation (i.e. brain conductivity distributions) and stimulation (e.g. coil positioning and orientations) setup have not been quantified. In this study, we construct a high-resolution anisotropic head model in standard ICBM space, which can be used as a population-representative standard for bioelectromagnetic simulations. Further, we employ Monte-Carlo simulations in order to quantify how uncertainties in conductivity values propagate all the way to induced field and currents, demonstrating significant, regionally dependent dispersions in values which are commonly assumed "ground truth". This framework can be leveraged in order to quantify the effect of any type of uncertainty in noninvasive brain stimulation and bears relevance in all applications of TMS, both investigative and therapeutic.

Comparison of spherical and realistically shaped boundary element head models for transcranial magnetic stimulation navigation

OBJECTIVE

MRI-guided real-time transcranial magnetic stimulation (TMS) navigators that apply electromagnetic modeling have improved the utility of TMS. However, their accuracy and speed depends on the assumed volume conductor geometry. Spherical models found in present navigators are computationally fast but may be inaccurate in some areas. Realistically shaped boundary-element models (BEMs) could increase accuracy at a moderate computational cost, but it is unknown which model features have the largest influence on accuracy. Thus, we compared different types of spherical models and BEMs.

METHODS

Globally and locally fitted spherical models and different BEMs with either one or three compartments and with different skull-to-brain conductivity ratios (1/1-1/80) were compared against a reference BEM.

RESULTS

The one-compartment BEM at inner skull surface was almost as accurate as the reference BEM. Skull/brain conductivity ratio in the range 1/10-1/80 had only a minor influence. BEMs were superior to spherical models especially in frontal and temporal areas (up to 20mm localization and 40% intensity improvement); in motor cortex all models provided similar results.

CONCLUSIONS

One-compartment BEMs offer a good balance between accuracy and computational cost.

SIGNIFICANCE

Realistically shaped BEMs may increase TMS navigation accuracy in several brain areas, such as in prefrontal regions often targeted in clinical applications.

The influence of sulcus width on simulated electric fields induced by transcranial magnetic 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.

Physiological observations validate finite element models for estimating subject-specific electric field distributions induced by transcranial magnetic stimulation of the human motor cortex

Recent evidence indicates subject-specific gyral folding patterns and white matter anisotropy uniquely shape electric fields generated by TMS. Current methods for predicting the brain regions influenced by TMS involve projecting the TMS coil position or center of gravity onto realistic head models derived from structural and functional imaging data. Similarly, spherical models have been used to estimate electric field distributions generated by TMS pulses delivered from a particular coil location and position. In the present paper we inspect differences between electric field computations estimated using the finite element method (FEM) and projection-based approaches described above. We then more specifically examined an approach for estimating cortical excitation volumes based on individualistic FEM simulations of electric fields. We evaluated this approach by performing neurophysiological recordings during MR-navigated motormapping experiments. We recorded motor evoked potentials (MEPs) in response to single pulse TMS using two different coil orientations (45° and 90° to midline) at 25 different locations (5×5 grid, 1cm spacing) centered on the hotspot of the right first dorsal interosseous (FDI) muscle in left motor cortex. We observed that motor excitability maps varied within and between subjects as a function of TMS coil position and orientation. For each coil position and orientation tested, simulations of the TMS-induced electric field were computed using individualistic FEM models and compared to MEP amplitudes obtained during our motormapping experiments. We found FEM simulations of electric field strength, which take into account subject-specific gyral geometry and tissue conductivity anisotropy, significantly correlated with physiologically observed MEP amplitudes (rmax=0.91, p=1.8×10(-5) rmean=0.81, p=0.01). These observations validate the implementation of individualistic FEM models to account for variations in gyral folding patterns and tissue conductivity anisotropy, which should help improve the targeting accuracy of TMS in the mapping or modulation of human brain circuits.

Optimal coil orientation for transcranial magnetic stimulation

We study the impact of coil orientation on the motor threshold (MT) and present an optimal coil orientation for stimulation of the foot. The result can be compared to results of models that predict this orientation from electrodynamic properties of the media in the skull and from orientations of cells, respectively. We used a robotized TMS system for precise coil placement and recorded motor-evoked potentials with surface electrodes on the abductor hallucis muscle of the right foot in 8 healthy control subjects. First, we performed a hot-spot search in standard (lateral) orientation and then rotated the coil in steps of 10° or 20°. At each step we estimated the MT. For navigated stimulation and for correlation with the underlying anatomy a structural MRI scan was obtained. Optimal coil orientation was 33.1±18.3° anteriorly in relation to the standard lateral orientation. In this orientation the threshold was 54±18% in units of maximum stimulator output. There was a significant difference of 8.0±5.9% between the MTs at optimal and at standard orientation. The optimal coil orientations were significantly correlated with the direction perpendicular to the postcentral gyrus (). Robotized TMS facilitates sufficiently precise coil positioning and orientation to study even small variations of the MT with coil orientation. The deviations from standard orientation are more closely matched by models based on field propagation in media than by models based on orientations of pyramidal cells.

Transcranial electric and magnetic stimulation: technique and paradigms

Transcranial electrical and magnetic stimulation techniques encompass a broad physical variety of stimuli, ranging from static magnetic fields or direct current stimulation to pulsed magnetic or alternating current stimulation with an almost infinite number of possible stimulus parameters. These techniques are continuously refined by new device developments, including coil or electrode design and flexible control of the stimulus waveforms. They allow us to influence brain function acutely and/or by inducing transient plastic after-effects in a range from minutes to days. Manipulation of stimulus parameters such as pulse shape, intensity, duration, and frequency, and location, size, and orientation of the electrodes or coils enables control of the immediate effects and after-effects. Physiological aspects such as stimulation at rest or during attention or activation may alter effects dramatically, as does neuropharmacological drug co-application. Non-linear relationships between stimulus parameters and physiological effects have to be taken into account.

Fast multigrid-based computation of the induced electric field for transcranial magnetic stimulation

In transcranial magnetic stimulation (TMS), the distribution of the induced electric field, and the affected brain areas, depends on the position of the stimulation coil and the individual geometry of the head and brain. The distribution of the induced electric field in realistic anatomies can be modelled using computational methods. However, existing computational methods for accurately determining the induced electric field in realistic anatomical models have suffered from long computation times, typically in the range of tens of minutes or longer. This paper presents a matrix-free implementation of the finite-element method with a geometric multigrid method that can potentially reduce the computation time to several seconds or less even when using an ordinary computer. The performance of the method is studied by computing the induced electric field in two anatomically realistic models. An idealized two-loop coil is used as the stimulating coil. Multiple computational grid resolutions ranging from 2 to 0.25 mm are used. The results show that, for macroscopic modelling of the electric field in an anatomically realistic model, computational grid resolutions of 1 mm or 2 mm appear to provide good numerical accuracy compared to higher resolutions. The multigrid iteration typically converges in less than ten iterations independent of the grid resolution. Even without parallelization, each iteration takes about 1.0 s or 0.1 s for the 1 and 2 mm resolutions, respectively. This suggests that calculating the electric field with sufficient accuracy in real time is feasible.