Transcranial Magnetic Stimulation Fields Research Articles

Advancing working memory research through cortico-cortical transcranial magnetic stimulation

The neural underpinnings of working memory (WM) have been of continuous scientific interest for decades. As the understanding of WM progresses and new theories, such as the distributed view of WM, develop, the need to advance the methods used to study WM also arises. This perspective discusses how building from the state-of-the-art in the field of transcranial magnetic stimulation (TMS), and utilising cortico-cortical TMS, may pave the way for testing some of the predictions proposed by the distributed WM view. Further, after briefly discussing current barriers that need to be overcome for implementing cortico-cortical TMS for WM research, examples of how cortico-cortical TMS may be employed in the context of WM research are provided, guided by the ongoing debate on the sensory recruitment framework.

A fast direct solver for surface-based whole-head modeling of transcranial magnetic stimulation

When modeling transcranial magnetic stimulation (TMS) in the brain, a fast and accurate electric field solver can support interactive neuronavigation tasks as well as comprehensive biophysical modeling. We formulate, test, and disseminate a direct (i.e., non-iterative) TMS solver that can accurately determine global TMS fields for any coil type everywhere in a high-resolution MRI-based surface model with ~ 200,000 or more arbitrarily selected observation points within approximately 5 s, with the solution time itself of 3 s. The solver is based on the boundary element fast multipole method (BEM-FMM), which incorporates the latest mathematical advancement in the theory of fast multipole methods—an FMM-based LU decomposition. This decomposition is specific to the head model and needs to be computed only once per subject. Moreover, the solver offers unlimited spatial numerical resolution. Despite the fast execution times, the present direct solution is numerically accurate for the default model resolution. In contrast, the widely used brain modeling software SimNIBS employs a first-order finite element method that necessitates additional mesh refinement, resulting in increased computational cost. However, excellent agreement between the two methods is observed for various practical test cases following mesh refinement, including a biophysical modeling task. The method can be readily applied to a wide range of TMS analyses involving multiple coil positions and orientations, including image-guided neuronavigation. It can even accommodate continuous variations in coil geometry, such as flexible H-type TMS coils. The FMM-LU direct solver is freely available to academic users.

Exploring research trends and focal points in the application of transcranial magnetic stimulation for enhancing motor function in post-stroke patients: A bibliometric and content analytical approach

BackgroundMotor impairment is a significant health concern among post-stroke patients. Transcranial magnetic stimulation (TMS) is considered as an emerging rehabilitation therapy for various neurological conditions, and the effects of excitatory TMS on post-stroke have received much attention in past decade. However, the future hotspots and content analysis on the growth trends have not been studied. This bibliometric and content analysis aimed to study the global developmental history and current status of TMS for motor function of post-stroke from January 2004 to July 2023. MethodsLiterature published on Scopus database from January 2004 to July 2023 were searched. Extracted data was analysed using the R studio and VOS viewer for author's publication, institutions, sources, keyword co-occurrence and world network analysis. Keyword cluster analysis, co-citation analysis for references and content analysis were also performed. We screened top 10 most cited or collaborative areas for publications, institutions and sources in the field of TMS associated with motor function of post-stroke. ResultsIn this study, a comprehensive analysis of 267 publications was conducted, revealing a substantial surge in research output throughout 2022. China emerged as the leading contributor, with 409 publications, followed by the United States with 211 publications. Notably, Harvard Medical School stood out as one of the most prolific institutions, accounting for 34 publications (13.12 %). Among researchers, Abo M garnered the highest publication count, with 9 articles (14.5 %). The Word cloud showed that motor function, repetitive transcranial magnetic stimulation (rTMS) and upper limb have been the focus of recent attention. Burst keywords on thematic evolution and topic trend shows that quality of life scale, network parameters, cognition, lower limb motor function are the future trends. ConclusionThis bibliometric study describes that TMS has shown promising results in improving motor function of upper extremity in stroke patients, the long-term effects and durability of these improvements are still being investigated. Future research might focus on understanding the optimal duration and frequency of TMS sessions for sustained motor recovery and exploring strategies to maintain gains achieved through TMS over extended periods of time. Future studies can investigate the changes in the lower limb motor function.

A Review of Formulations, Boundary Value Problems and Solutions for Numerical Computation of Transcranial Magnetic Stimulation Fields.

Since the inception of the transcranial magnetic stimulation (TMS) technique, it has become imperative to numerically compute the distribution of the electric field induced in the brain. Various models of the coil-brain system have been proposed for this purpose. These models yield a set of formulations and boundary conditions that can be employed to calculate the induced electric field. However, the literature on TMS simulation presents several of these formulations, leading to potential confusion regarding the interpretation and contribution of each source of electric field. The present study undertakes an extensive compilation of widely utilized formulations, boundary value problems and numerical solutions employed in TMS fields simulations, analyzing the advantages and disadvantages associated with each used formulation and numerical method. Additionally, it explores the implementation strategies employed for their numerical computation. Furthermore, this work provides numerical expressions that can be utilized for the numerical computation of TMS fields using the finite difference and finite element methods. Notably, some of these expressions are deduced within the present study. Finally, an overview of some of the most significant results obtained from numerical computation of TMS fields is presented. The aim of this work is to serve as a guide for future research endeavors concerning the numerical simulation of TMS.

Modeling transcranial magnetic stimulation coil with magnetic cores

Objective. Accurate modeling of transcranial magnetic stimulation (TMS) coils with the magnetic core is largely an open problem since commercial (quasi) magnetostatic solvers do not output specific field characteristics (e.g. induced electric field) and have difficulties when incorporating realistic head models. Many open-source TMS softwares do not include magnetic cores into consideration. This present study reports an algorithm for modeling TMS coils with a (nonlinear) magnetic core and validates the algorithm through comparison with finite-element method simulations and experiments. Approach. The algorithm uses the boundary element fast multipole method applied to all facets of a tetrahedral core mesh for a single-state solution and the successive substitution method for nonlinear convergence of the subsequent core states. The algorithm also outputs coil inductances, with or without magnetic cores. The coil–core combination is solved only once i.e. before incorporating the head model. The resulting primary TMS electric field is proportional to the total vector potential in the quasistatic approximation; it therefore also employs the precomputed core magnetization. Main results. The solver demonstrates excellent convergence for typical TMS field strengths and for analytical B–H approximations of experimental magnetization curves such as Froelich’s equation or an arctangent equation. Typical execution times are 1–3 min on a common multicore workstation. For a simple test case of a cylindrical core within a one-turn coil, our solver computed the small-signal inductance nearly identical to that from ANSYS Maxwell. For a multiturn rodent TMS coil with a core, the modeled inductance matched the experimental measured value to within 5%. Significance. Incorporating magnetic core in TMS coil design has advantages of field shaping and energy efficiency. Our software package can facilitate model-informed design of more efficiency TMS systems and guide selection of core material. These models can also inform dosing with existing clinical TMS systems that use magnetic cores.

Transcranial Magnetic Stimulation during Gait: A Review of Methodological and Technological Challenges.

Transcranial magnetic stimulation (TMS) is widely used for therapeutic and research purposes such as cognitive studies, treatment of psychiatric disorders, and Parkinson's disease. In research, TMS is perhaps the only technique that can establish a functional connection between brain regions and task performance. In gait research, often TMS is used to identify the extent to which leg motor cortex is involved in different phases on gait cycle. However, using TMS in gait can be challenging for several technical reasons and physiological variations. The objective of this narrative review is to summarize literature in the field of TMS and gait research and present comprehensive challenges. A comprehensive literature search was conducted in PubMed and Google Scholar to identify all relevant literature on TMS and gait. Several critical challenges could potentially impact the findings. For instance, the use of different protocols to obtain motor threshold. This review presents some of the critical challenges in applying TMS during gait. It is important to be aware of these variations and utilize strategies to mitigate some challenges.

TMS activation site estimation using multiscale realistic head models

Objective. Transcranial magnetic stimulation (TMS) activates brain structures non-invasively. Computational models can be used to elucidate the activation site; however, the exact activation site is controversial. The aim is to present an imaging technique of the TMS activation cortical site estimation using individualized multi-scale realistic head models based on experimentally-derived TMS fields. Approach. The induced electric field (EF) was computed using subject-specific head models and experimental-specific TMS coil configuration during suprathreshold stimulation for relaxed muscles. The experimentally-derived EFs were used to calculate the activation of pyramidal tract model embedded in the head models to derive the activation site on the cortical surface at the macroscopic level. Main results. The TMS activation site was located at the anterior wall of the central sulcus, which agreed with a concurrent TMS/fMRI study. In contrast, the EF strength was not entirely consistent with TMS/fMRI studies. Multiscale physical modelling is a feasible imaging technique to investigate the activation site for TMS. Significance. By combining subject-specific multiscale modelling with experimental TMS measurements, we showed that this method could serve as a TMS imaging technique at suprathreshold condition.

Electric field simulations for transcranial brain stimulation using FEM: an efficient implementation and error analysis

Objective. Transcranial magnetic stimulation (TMS) and transcranial electric stimulation (TES) modulate brain activity non-invasively by generating electric fields either by electromagnetic induction or by injecting currents via skin electrodes. Numerical simulations based on anatomically detailed head models of the TMS and TES electric fields can help us to understand and optimize the spatial stimulation pattern in the brain. However, most realistic simulations are still slow, and the role of anatomical fidelity on simulation accuracy has not been evaluated in detail so far. Approach. We present and validate a new implementation of the finite element method (FEM) for TMS and TES that is based on modern algorithms and libraries. We also evaluate the convergence of the simulations and estimate errors stemming from numerical and modelling aspects. Main results. Comparisons with analytical solutions for spherical phantoms validate our new FEM implementation, which is three to six times faster than previous implementations. The convergence results suggest that accurately capturing the tissue geometry in addition to choosing a sufficiently accurate numerical method is of fundamental importance for accurate simulations. Significance. The new implementation allows for a substantial increase in computational efficiency of FEM TMS and TES simulations. This is especially relevant for applications such as the systematic assessment of model uncertainty and the optimization of multi-electrode TES montages. The results of our systematic error analysis allow the user to select the best tradeoff between model resolution and simulation speed for a specific application. The new FEM code is openly available as a part of our open-source software SimNIBS 3.0.

Comparative modeling of transcranial magnetic and electric stimulation in mouse, monkey, and human

Transcranial magnetic stimulation (TMS) and transcranial electric stimulation (TES) are increasingly popular methods to noninvasively affect brain activity. However, their mechanism of action and dose-response characteristics remain under active investigation. Translational studies in animals play a pivotal role in these efforts due to a larger neuroscientific toolset enabled by invasive recordings. In order to translate knowledge gained in animal studies to humans, it is crucial to generate comparable stimulation conditions with respect to the induced electric field in the brain. Here, we conduct a finite element method (FEM) modeling study of TMS and TES electric fields in a mouse, capuchin and macaque monkeys, and a human model. We systematically evaluate the induced electric fields and analyze their relationship to head and brain anatomy. We find that with increasing head size, TMS-induced electric field strength first increases and then decreases according to a two-term exponential function. TES-induced electric field strength strongly decreases from smaller to larger specimen with up to 100x fold differences across species. Our results can serve as a basis to compare and match stimulation parameters across studies in animals and humans.

A principled approach to conductivity uncertainty analysis in electric field calculations

Uncertainty surrounding ohmic tissue conductivity impedes accurate calculation of the electric fields generated by non-invasive brain stimulation. We present an efficient and generic technique for uncertainty and sensitivity analyses, which quantifies the reliability of field estimates and identifies the most influential parameters. For this purpose, we employ a non-intrusive generalized polynomial chaos expansion to compactly approximate the multidimensional dependency of the field on the conductivities. We demonstrate that the proposed pipeline yields detailed insight into the uncertainty of field estimates for transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS), identifies the most relevant tissue conductivities, and highlights characteristic differences between stimulation methods. Specifically, we test the influence of conductivity variations on (i) the magnitude of the electric field generated at each gray matter location, (ii) its normal component relative to the cortical sheet, (iii) its overall magnitude (indexed by the 98th percentile), and (iv) its overall spatial distribution. We show that TMS fields are generally less affected by conductivity variations than tDCS fields. For both TMS and tDCS, conductivity uncertainty causes much higher uncertainty in the magnitude as compared to the direction and overall spatial distribution of the electric field. Whereas the TMS fields were predominantly influenced by gray and white matter conductivity, the tDCS fields were additionally dependent on skull and scalp conductivities. Comprehensive uncertainty analyses of complex systems achieved by the proposed technique are not possible with classical methods, such as Monte Carlo sampling, without extreme computational effort. In addition, our method has the advantages of directly yielding interpretable and intuitive output metrics and of being easily adaptable to new problems.

The challenges of producing effective small coils for transcranial magnetic stimulation of mice

Introduction. Transcranial magnetic stimulation (TMS) is used for treating neurological disorders. Rapid pulses of magnetic field are delivered via a high-current coil situated over the scalp and induce an electric field in the brain. There has been limited fundamental scientific research on TMS and to progress it would be ideal to mimic the electric field of human TMS with mice. Animal models provide good mechanistic insight, but their use is hindered by lack of stimulating coils comparable in focus and intensity with human stimulation. Methods. We outline the engineering challenges in producing appropriate coils. It is unclear what should be optimized in the design of a mouse coil. We model the electric field, heat generation and ring-down time for cylindrical coils and use results to select a coil design consisting of 70 turns of 0.4 mm diameter copper wire wrapped around a 5 mm diameter soft ferrite core. Results and Discussion. While the magnetic flux density scales as the reciprocal of length-scale, the electric field does not scale with length, meaning that a large current is required to mimic the electric field of humans. To maximize electric field, one must minimize the coil’s inductance resulting in reduced ring-down time for the coil and significant heating. A ferrite core allows ring-down time to remain high and reduces heating. Our coil gave 180 mT at 30 V supply, with a temperature increase of 5°C after 1200 pulses at 5 Hz. The B-field below the core has a full-width-at-half-maximum of 6 mm, similar in size to a mouse brain. Conclusions. We have produced a mouse coil that offers increased B-field and reduced heating. There is considerable scope for improving electric field, but further physical analysis may lead to field strength more similar to that obtained in human TMS.

Static Field Influences on Transcranial Magnetic Stimulation: Considerations for TMS in the Scanner Environment

Transcranial magnetic stimulation (TMS) can be combined with functional magnetic resonance imaging (fMRI) to simultaneously manipulate and monitor human cortical responses. Although tremendous efforts have been directed at characterizing the impact of TMS on image acquisition, the influence of the scanner's static field on the TMS coil has received limited attention. The aim of this study was to characterize the influence of the scanner's static field on TMS. We hypothesized that spatial variations in the static field could account for TMS field variations in the scanner environment. Using an MRI-compatible TMS coil, we estimated TMS field strengths based on TMS-induced voltage changes measured in a search coil. We compared peak field strengths obtained with the TMS coil positioned at different locations (B0 field vs fringe field) and orientations in the static field. We also measured the scanner's static field to derive a field map to account for TMS field variations. TMS field strength scaled depending on coil location and orientation with respect to the static field. Larger TMS field variations were observed in fringe field regions near the gantry as compared to regions inside the bore or further removed from the bore. The scanner's static field also exhibited the greatest spatial variations in fringe field regions near the gantry. The scanner's static field influences TMS fields and spatial variations in the static field correlate with TMS field variations. Coil orientation changes in the B0 field did not result in substantial TMS field variations. TMS field variations can be minimized by delivering TMS in the bore or outside of the 0-70cm region from the bore entrance.

IS 3. TMS field modelling-status and next steps

In the recent years, an increasing number of studies used geometrically accurate head models and finite element (FEM) or finite difference methods (FDM) to estimate the electric field induced by non-invasive neurostimulation techniques such as transcranial magnetic stimulation (TMS) or transcranial weak current stimulation (tCS; e.g., Datta et al., 2010, Thielscher et al., 2011). A general outcome was that the field estimates based on these more realistic models differ substantially from the results obtained with simpler head models. This suggests that the former models are indeed needed to realistically capture the field distribution in the brain. However, it is unclear how accurate even these more advanced models are and, in particular, to which extent they allow predicting the physiological outcome of stimulation. An experimental validation of the novel methods for field calculation is thus necessary. Focusing on motor cortex stimulation by TMS, our goal is to explore to which extent the field estimates based on advanced models correlate with the physiological stimulation effects. For example, we aim at testing whether interindividual differences in the field estimates are also reflected in differences in the MEP responses. This would indicate that the field calculations accurately capture the impact of individual macroanatomical features of the head and brain on the induced field distribution, in turn strongly supporting their plausibility. Our approach is based on the SimNIBS software pipeline (www.simnibs.de) that allows for the automatic creation of accurate head models from structural and diffusion-weighted magnetic resonance images (MRI) (Windhoff et al., 2011). This enables us to perform field calculations for multiple subjects, as required in neuroscientific studies. We substantially improved the software in order to improve its usability in a group analysis. At the moment, we are performing field calculations and are acquiring motor mapping data in a group of subjects for a systematic comparison of both data sets. I will give an overview on the status of the SimNIBS project. I will start by summarizing the key findings on how the individual brain anatomy shapes the electric field induced by TMS Thielscher et al., 2011, Opitz, 2011. The putative link between the modeling results and basic physiological TMS effects is highlighted. I will then introduce the novel features of SimNIBS that include the import of coil positions from neuronavigation systems, improved support for diffusion-weighted MRI and transformation of the estimated fields into MNI space for group analysis. Preliminary results on the comparison between field estimates and motor mapping data will be presented. To summarize, field estimates based on accurate head models have already proven highly useful for a better understanding of the biophysics of non-invasive brain stimulation. The improved software tools now allow for systematic tests of the links between the estimated fields and the physiological effects in multi-subject studies. This will give the knowledge needed, e.g., for a more accurate spatial targeting of specific brain areas by TMS.

Impact of brain tissue filtering on neurostimulation fields: A modeling study

Electrical neurostimulation techniques, such as deep brain stimulation (DBS) and transcranial magnetic stimulation (TMS), are increasingly used in the neurosciences, e.g., for studying brain function, and for neurotherapeutics, e.g., for treating depression, epilepsy, and Parkinson's disease. The characterization of electrical properties of brain tissue has guided our fundamental understanding and application of these methods, from electrophysiologic theory to clinical dosing-metrics. Nonetheless, prior computational models have primarily relied on ex-vivo impedance measurements. We recorded the in-vivo impedances of brain tissues during neurosurgical procedures and used these results to construct MRI guided computational models of TMS and DBS neurostimulatory fields and conductance-based models of neurons exposed to stimulation. We demonstrated that tissues carry neurostimulation currents through frequency dependent resistive and capacitive properties not typically accounted for by past neurostimulation modeling work. We show that these fundamental brain tissue properties can have significant effects on the neurostimulatory-fields (capacitive and resistive current composition and spatial/temporal dynamics) and neural responses (stimulation threshold, ionic currents, and membrane dynamics). These findings highlight the importance of tissue impedance properties on neurostimulation and impact our understanding of the biological mechanisms and technological potential of neurostimulatory methods.

Álvaro Pascual-Leone: a pioneer of non-invasive brain stimulation

Álvaro Pascual-Leone: a pioneer of non-invasive brain stimulation

Multi-channel NIRS of the primary motor cortex to discriminate hand from foot activity

The poor spatial resolution of near-infrared spectroscopy (NIRS) makes it difficult to distinguish two closely located cortical areas from each other. Here, a combination of multi-channel NIRS and a centre of gravity (CoG) approach (widely accepted in the field of transcranial magnetic stimulation; TMS) was used to discriminate between closely located cortical areas activated during hand and foot movements. Similarly, the possibility of separating the more anteriorly represented discrete movements from rhythmic movements was studied. Thirteen healthy right-handed subjects performed rhythmic or discrete (‘task’) hand or foot (‘extremity’) tapping. Hemodynamic responses were measured using an 8-channel NIRS setup. For oxyhemoglobin (OHb) and deoxyhemoglobin (HHb), a CoG was determined for each condition using the mean hemodynamic responses and the coordinates of the channels. Significant hemodynamic responses were found for hand and foot movements. Based on the HHb responses, the NIRS-CoG of hand movements was located 0.6 cm more laterally compared to the NIRS-CoG of foot movements. For OHb responses no difference in NIRS-CoG was found for ‘extremity’ nor for ‘task’. This is the first NIRS study showing hemodynamic responses for isolated foot movements. Furthermore, HHb responses have the potential to be used in multi-channel NIRS experiments requiring differential activation of motor cortex areas linked to either hand or foot movements.

State-Dependency Effects on TMS: A Look at Motive Phosphene Behavior

Transcranial magnetic stimulation (TMS) is a non-invasive neurostimulatory and neuromodulatory technique that can transiently or lastingly modulate cortical excitability (either increasing or decreasing it) via the application of localized magnetic field pulses. Within the field of TMS, the term state dependency refers to the initial, baseline condition of the particular neural region targeted for stimulation. As can be inferred, the effects of TMS can (and do) vary according to this primary susceptibility and responsiveness of the targeted cortical area. In this experiment, we will examine this concept of state dependency through the elicitation and subjective experience of motive phosphenes. Phosphenes are visually perceived flashes of small lights triggered by electromagnetic pulses to the visual cortex. These small lights can assume varied characteristics depending upon which type of visual cortex is being stimulated. In this particular study, we will be targeting motive phosphenes as elicited through the stimulation of V1/V2 and the V5/MT+ complex visual regions.

Aspetti neurofisiologici e neuropsichiatrici della stimolazione magnetica transcranica

Introduction The authors review the literature in the field of Transcranial Magnetic Stimulation (TMS). Materials and methods For this purpose a PubMed search was performed. Additional information was gained by cross-referencing from papers found in the data base. Results Data from controlled studies as well as supplementary information from relevant review articles pertinent to the topic were used. History and the basics of TMS and repetitive Transcranial Magnetic Stimulation (rTMS) are presented. The ability of rTMS to non-invasively modulate higher cognitive functions such as learning and memory developed to a new exciting field. TMS, in fact, allows to transiently disrupt ongoing cortical processing, thus helping to enlighten the causal role of a specific brain area in a certain observable behaviour. Finally, rTMS clinical effectiveness in mood disorders, anxiety disorders, schizophrenic psychoses and Parkinson's disease, as well as in pain syndrome, is discussed. Conclusions RTMS in concert with functional neuroimaging methods allows to analyse neuronal networks. Long-Term Potentiation (LTP) and Long-Term Depression (LTD) are phenomena seen in preclinical studies after rTMS, thus reflecting plastic modulation of the brain. In fact, changes in brain plasticity are supposed to be putative mechanisms underlying the pathophysiology of psychiatric diseases like major depression.

Consensus paper: Combining transcranial stimulation with neuroimaging

In the last decade, combined transcranial magnetic stimulation (TMS)-neuroimaging studies have greatly stimulated research in the field of TMS and neuroimaging. Here, we review how TMS can be combined with various neuroimaging techniques to investigate human brain function. When applied during neuroimaging (online approach), TMS can be used to test how focal cortex stimulation acutely modifies the activity and connectivity in the stimulated neuronal circuits. TMS and neuroimaging can also be separated in time (offline approach). A conditioning session of repetitive TMS (rTMS) may be used to induce rapid reorganization in functional brain networks. The temporospatial patterns of TMS-induced reorganization can be subsequently mapped by using neuroimaging methods. Alternatively, neuroimaging may be performed first to localize brain areas that are involved in a given task. The temporospatial information obtained by neuroimaging can be used to define the optimal site and time point of stimulation in a subsequent experiment in which TMS is used to probe the functional contribution of the stimulated area to a specific task. In this review, we first address some general methodologic issues that need to be taken into account when using TMS in the context of neuroimaging. We then discuss the use of specific brain mapping techniques in conjunction with TMS. We emphasize that the various neuroimaging techniques offer complementary information and have different methodologic strengths and weaknesses.

Magnetism on the Brain

FOR YEARS, SCIENTISTS AND PHYSIcians have been trying to tap into the brain to investigate and manipulate the neurons that make up its intricate circuitry. Such studies have sought, for example, to understand how thoughts are formed, to find ways to relieve intractable depression, and to block the neurodegeneration of such conditions as Alzheimer and Huntington diseases. One technique, transcranial magnetic stimulation (TMS), has been used by many scientists to turn on and off particular parts of the brain in research efforts. The technique has also been investigated as a possible therapeutic alternative to electroconvulsive therapy (ECT) for depression. But TMS, which was developed in the 1980s, has been slow to catch on as a viable therapy for psychiatric and neurological conditions because its effects have been small, variable, and short-term. Now, new research has demonstrated that TMS can be manipulated to produce more consistent and longerlasting changes in the brain. The findings have prompted some scientists to predict that the technique may eventually find a place in the clinic. It’s easy to understand why TMS has been considered a form of brain stimulation worth investigating for its therapeutic potential. Unlike such techniques as ECT or deep brain stimulation, it is not convulsive and does not require anesthesia or implanting devices within the brain. “This is very easy to apply, it’s noninvasive, and it doesn’t hurt,” said John Rothwell, PhD, of the Institute of Neurology at University College London, in London, England. The technique uses a magnetic coil housed inside a paddle that is held near the scalp. This coil produces a magnetic field that induces small electrical currents within the brain; dependingon the timingof treatment, it can either excite or suppress neurons directly beneath the paddle. But the technology’s limitations have tempered enthusiasm about its therapeutic potential. TMS fields do not penetrate deep into the brain, and researchers found that the excitatory or inhibitory effects on neurons rarely lasted longer than 30 minutes. Those limitations may not be insurmountable, however. Rothwell’s latest study has shown that TMS can be manipulated to produce rapid, consistent, and controllable changes in the brain that last twice as long as those produced by conventional TMS (Huang et al. Neuron. 2005;45:201-206). The findings, the researchers say, suggest that TMS may one day go beyond being a powerful research tool to become a potential therapy for a variety of brain conditions as well. TMS FOR DEPRESSION