Transcranial Magnetic Stimulation Coil Research Articles

Verification of neuronavigated TMS accuracy using structured-light 3D scans

Objective. To investigate the reliability and accuracy of the manual three-point co-registration in neuronavigated transcranial magnetic stimulation (TMS). The effect of the error in landmark pointing on the coil placement and on the induced electric and magnetic fields was examined. Approach. The position of the TMS coil on the head was recorded by the neuronavigation system and by 3D scanning for ten healthy participants. The differences in the coil locations and orientations and the theoretical error values for electric and magnetic fields between the neuronavigated and 3D scanned coil positions were calculated. In addition, the sensitivity of the coil location on landmark accuracy was calculated. Main results. The measured distances between the neuronavigated and 3D scanned coil locations were on average 10.2 mm, ranging from 3.1 to 18.7 mm. The error in angles were on average from two to three degrees. The coil misplacement caused on average a 29% relative error in the electric field with a range from 9% to 51%. In the magnetic field, the same error was on average 33%, ranging from 10% to 58%. The misplacement of landmark points could cause a 1.8-fold error for the coil location. Significance. TMS neuronavigation with three landmark points can cause a significant error in the coil position, hampering research using highly accurate electric field calculations. Including 3D scanning to the process provides an efficient method to achieve a more accurate coil position.

Field recordings of transcranial magnetic stimulation in human brain postmortem models.

The ability of repetitive transcranial magnetic stimulation (rTMS) to deliver a magnetic field (MF) in deep brain targets is debated and poorly documented. To quantify the decay of MF in the human brain. Magnetic field was generated by single pulses of TMS delivered at maximum intensity using a flat or angulated coil. Magnetic field was recorded by a 3D-magnetic probe. Decay was measured in the air using both coils and in the head of 10 postmortem human heads with the flat coil being positioned tangential to the scalp. Magnetic field decay was interpreted as a function of distance to the coil for 6 potential brain targets of noninvasive brain stimulation: the primary motor cortex (M1, mean depth: 28.5 mm), dorsolateral prefrontal cortex (DLPFC: 28 mm), secondary somatosensory cortex (S2: 35.5 mm), posterior and anterior insulae (PI: 38.5 mm; AI: 43.5 mm), and midcingulate cortex (MCC: 57.5 mm). In air, the maximal MF intensities at coil center were 0.88 and 0.77 T for the flat and angulated coils, respectively. The maximal intracranial MF intensity in the cadaver model was 0.34 T, with a ∼50% decay at 15 mm and a ∼75% MF decay at 30 mm. The decay of the MF in air was similar for the flat coil and significantly less attenuated with the angulated coil (a ∼50% decay at 20 mm and a ∼75% MF decay at 45 mm). Transcranial magnetic stimulation coil MFs decay in brain structures similarly as in air, attenuation with distance being significantly lower with angulated coils. Reaching brain targets deeper than 20 mm such as the insula or Antérior Cingulate Cortex seems feasible only when using angulated coils. The abacus of MF attenuation provided here can be used to adjust modalities of deep brain stimulation with rTMS in future research protocols.

Bypassing input to V1 in visual awareness: A TMS-EROS investigation

Early visual cortex (V1–V3) is believed to be critical for normal visual awareness by providing the necessary feedforward input. However, it remains unclear whether visual awareness can occur without further involvement of early visual cortex, such as re-entrant feedback. It has been challenging to determine the importance of feedback activity to these areas because of the difficulties in dissociating this activity from the initial feedforward activity. Here, we applied single-pulse transcranial magnetic stimulation (TMS) over the left posterior parietal cortex to elicit phosphenes in the absence of direct visual input to early visual cortex. Immediate neural activity after the TMS pulse was assessed using the event-related optical signal (EROS), which can measure activity under the TMS coil without artifacts. Our results show that: 1) The activity in posterior parietal cortex 50 ms after TMS was related to phosphene awareness, and 2) Activity related to awareness was observed in a small portion of V1 140 ms after TMS, but in contrast (3) Activity in V2 was a more robust correlate of awareness. Together, these results are consistent with interactive models proposing that sustained and recurrent loops of activity between cortical areas are necessary for visual awareness to emerge. In addition, we observed phosphene-related activations of the anteromedial cuneus and lateral occipital cortex, suggesting a functional network subserving awareness comprising these regions, the parietal cortex and early visual cortex.

Research on the brain phantom for transcranial electromagnetic neuromodulation

Transcranial magnetic stimulation (TMS), a widely used neuroregulatory technique, has been proven to be effective in treating neurological and psychiatric disorders. The therapeutic effect is closely related to the intracranial electric field caused by TMS, thus accurate measurement of the intracranial electric field generated by TMS is of great significance. However, direct intracranial measurement in human brain faces various technical, safety, ethical and other limitations. Therefore, we have constructed a brain phantom that can simulate the electrical conductivity and anatomical structure of the real brain, in order to replace the clinical trial to achieve intracranial electric field measurement. We selected and prepared suitable conductive materials based on the electrical conductivity of various layers of the real brain tissue, and performed image segmentation, three-dimensional reconstruction and three-dimensional printing processes on each layer of tissue based on magnetic resonance images. The production of each layer of tissue in the brain phantom was completed, and each layer of tissue was combined to form a complete brain phantom. The induced electric field generated by the TMS coil applied to the brain phantom was measured to further verify the conductivity of the brain phantom. Our study provides an effective experimental tool for studying the distribution of intracranial electric fields caused by TMS.

Distinct neuronal circuits mediate cortical hyperexcitability in amyotrophic lateral sclerosis.

Cortical hyperexcitability is an important pathophysiological mechanism in amyotrophic lateral sclerosis (ALS), reflecting a complex interaction of inhibitory and facilitatory interneuronal processes that evolves in the degenerating brain. The advances in physiological techniques have made it possible to interrogate progressive changes in the motor cortex. Specifically, the direction of transcranial magnetic stimulation (TMS) stimulus within the primary motor cortex can be utilised to influence descending corticospinal volleys and to thereby provide information about distinct interneuronal circuits. Cortical motor function and cognition was assessed in 29 ALS patients with results compared to healthy volunteers. Cortical dysfunction was assessed using threshold-tracking TMS to explore alterations in short interval intracortical inhibition (SICI), short interval intracortical facilitation (SICF), the index of excitation (IE), and stimulus response (SR) curves using a figure-of-eight coil with the coil oriented relative to the primary motor cortex in a posterior-anterior (PA), lateral-medial (LM), and anterior-posterior (AP) direction. Mean SICI, between interstimulus interval (ISI) of 1-to-7 ms, was significantly reduced in ALS patients compared to healthy controls when assessed with the coil oriented in PA (P = 0.044) and LM (P = 0.005) but not the AP (P = 0.08) directions. A significant correlation between mean SICI oriented in a PA direction and the total Edinburgh Cognitive and Behavioural ALS Screen score (Rho = 0.389, P = 0.037) was evident. In addition, the mean SICF, between ISI 1-to-5 ms, was significantly increased in ALS patients when recorded with TMS coil oriented in PA (P = 0.035) and LM (P < 0.001) directions. In contrast, SICF recorded with TMS coil oriented in the AP direction was comparable between ALS and controls (P = 0.482). The IE was significantly increased in ALS patients when recorded with the TMS coil oriented in PA (P = 0.041) and LM (P = 0.003) directions. In ALS patients, a significant increase in the SR curve gradient was evident compared to controls when recorded with TMS coil oriented in PA (P < 0.001), LM (P < 0.001) and AP (P = 0.002) directions. The present study has established that dysfunction of distinct interneuronal circuits mediates the development of cortical hyperexcitability in ALS. Specifically, complex interplay between inhibitory circuits and facilitatory interneuronal populations, that are preferentially activated by stimulation in posterior-to-anterior or lateral-to-medial directions, promotes cortical hyperexcitability in ALS. Mechanisms that underlie dysfunction of these specific cortical neuronal circuits will enhance understanding of the pathophysiological processes in ALS, with the potential to uncover focussed therapeutic targets.

Transcranial magnetic stimulation over supramarginal gyrus stimulates primary motor cortex directly and impairs manual dexterity: implications for TMS focality.

Based on human motor cortex, the effective spatial resolution of transcranial magnetic stimulation (TMS) is often described as 5-20 mm, because small changes in TMS coil position can have large effects on motor-evoked potentials (MEPs). MEPs are often studied at rest, with muscles relaxed. During muscle contraction and movement, corticospinal excitability is higher, thresholds for effective stimulation are lower, and MEPs can be evoked from larger regions of scalp, so the effective spatial resolution of TMS is larger. We found that TMS over the supramarginal gyrus (SMG) impaired manual dexterity in the grooved pegboard task. It also resulted in short-latency MEPs in hand muscles, despite the coil being 55 mm away from the motor cortex hand area (M1). MEPs might be evoked by either a specific corticospinal connection from SMG or a remote but direct electromagnetic stimulation of M1. To distinguish these alternatives, we mapped MEPs across the scalp during rest, isotonic contraction, and manual dexterity tasks and ran electric field simulations to model the expected M1 activation from 27 scalp locations and four coil orientations. We also systematically reviewed studies using TMS during movement. Across five experiments, TMS over SMG reliably evoked MEPs during hand movement. These MEPs were consistent with direct M1 stimulation and substantially decreased corticospinal thresholds during natural movement. Systematic review suggested that 54 published experiments may have suffered from similar motor activation confounds. Our results have implications for the assumed spatial resolution of TMS, and especially when TMS is presented within 55 mm of the motor cortex.NEW & NOTEWORTHY Transcranial magnetic stimulation (TMS) is often described as having an effective spatial resolution of ∼10 mm, because of the limited area of the scalp on which TMS produces motor-evoked potentials (MEPs) in resting muscles. We find that during natural hand movement TMS evokes MEPs from a much larger scalp area, in particular when stimulating over the supramarginal gyrus 55 mm away. Our results show that TMS can be effective at much larger distances than generally assumed.

Novel multi-magnetic material transcranial magnetic stimulation coils for small animals application

Transcranial magnetic stimulation (TMS) is a non-invasive therapeutic approach with proven efficacy in treating certain psychiatric and neurological disorders. To broaden the application of TMS to a wider range of neurological disorders, the induced electric field (e-field) must be able to more focally target specific regions of the brain. Animal coil designs are promising for studying TMS effects and developing new procedures for treating various neurological and psychiatric disorders. However, investigations have mostly used coil designs intended for humans, and, as such, have failed to scale down for small animal sizes. Currently available coil systems have been limited by not adequately incorporating ideal soft magnetic materials as coil cores and not advancing the coil shapes for small animals as is necessary to achieve highly focused e-field concentration. In this study, we used multi-magnetic materials in TMS coils for the first time to our knowledge. We also considered the non-linear, hysteretic behavior of the cores in our FEM simulations of induced e-field and magnetic field in the brain models of the rat. Our study involved a comprehensive assessment of the distribution and intensity of the e-field across various coil configurations using our customized anatomically accurate rat head model. Iron-cobalt-vanadium (Permendur) alloy known for its high relative permeability, high saturation magnetization and low coercivity was used as the core material for all simulations. To enhance coil focality and concentration of the e-field, while avoiding stimulation of adjacent regions, we introduced a shape-conforming, flexible, diamagnetic pyrolytic graphite with susceptibility of -4.5×10-4 for our top performing coil. Simulation results were validated by comparing the simulated magnetic field results with experimental measurements obtained from the v-tip coil with a carbon steel AISI-1010 core at varying tip distances. This thorough study advances our knowledge of TMS coil designs and their optimization, particularly for small animal applications.

Optimizing a deep learning model for the prediction of electric field induced by transcranial magnetic stimulation for mild to moderate traumatic brain injury patients

Transcranial magnetic stimulation (TMS) is a non-invasive method for treating neurological and psychiatric disorders. It is being tested as an experimental treatment for patients with mild to moderate traumatic brain injuries (mTBI). Due to the complex, heterogeneous composition of the brain, it is difficult to determine if targeted brain regions receive the correct amount of electric field (E-field) induced by the TMS coil. E-field distributions can be calculated by running time-consuming finite element analysis (FEA) simulations of TMS on patient head models. Using machine learning, the E-field can be predicted in real-time. Our prior work used a Deep Convolutional Neural Network (DCNN) to predict the E-field in healthy patients. This study applies the same DCNN to mTBI patients and investigates how model depth and color space of E-field images affect model performance. Nine DCNNs were created using combinations of 3, 4, or 5 encoder and decoder blocks with the color spaces RGB, LAB, and YCbCr. As depth increased, training and testing peak signal-to-noise ratios (PSNR) increased and mean squared errors (MSE) decreased. The depth 5 YCbCr model had the highest training and testing PSNRs of 34.77 and 29.08 dB and lowest training and testing MSEs of 3.335∗10−4 and 1.237∗10−3 respectively. Compared to the model in our prior work, models of depth 5 have higher testing PSNRs and lower MSEs and, except for RGB. Thus, DCNNs with depth 5 and alternative color spaces, despite losing information through color space conversions, resulted in higher PSNRs and lower MSEs.

M2M-InvNet: Human Motor Cortex Mapping From Multi-Muscle Response Using TMS and Generative 3D Convolutional Network.

Transcranial magnetic stimulation (TMS) is often applied to the motor cortex to stimulate a collection of motor evoked potentials (MEPs) in groups of peripheral muscles. The causal interface between TMS and MEP is the selective activation of neurons in the motor cortex; moving around the TMS 'spot' over the motor cortex causes different MEP responses. A question of interest is whether a collection of MEP responses can be used to identify the stimulated locations on the cortex, which could potentially be used to then place the TMS coil to produce chosen sets of MEPs. In this work we leverage our previous report on a 3D convolutional neural network (CNN) architecture that predicted MEPs from the induced electric field, to tackle an inverse imaging task in which we start with the MEPs and estimate the stimulated regions on the motor cortex. We present and evaluate five different inverse imaging CNN architectures, both conventional and generative, in terms of several measures of reconstruction accuracy. We found that one architecture, which we propose as M2M-InvNet, consistently achieved the best performance.

Rodent Transcranial Magnetic Stimulation Coil Structure With Controllable Induction Electric Field Direction

Rodent Transcranial Magnetic Stimulation Coil Structure With Controllable Induction Electric Field Direction

Design of Transcranial Magnetic Stimulation Coils With Optimized Stimulation Depth

Design of Transcranial Magnetic Stimulation Coils With Optimized Stimulation Depth

Evaluating real-world effectiveness of accelerated transcranial magnetic stimulation for treatment-resistant depression in a tertiary referral center based in Quebec, Canada

ObjectiveTo assess the effectiveness of accelerated transcranial magnetic stimulation (TMS) for treatment-resistant depression (TRD) in a tertiary referral center in Quebec, Canada, focusing on a real-world clinical setting. MethodsWe reviewed the data of 247 TRD patients treated between January 2012 and May 2022 who received accelerated TMS. Participants were adults diagnosed with unipolar or bipolar depression, resistant to at least two antidepressant trials, and assessed using the Montgomery-Åsberg Depression Rating Scale (MADRS). ResultsSignificant symptom reduction was found in the completer sample (N = 147), with 46.3 % of patients meeting post-treatment response criteria and 36.1 % achieving remission. Baseline severity of depression, age, and the number of antidepressant trials were key predictors of treatment outcomes. Patients who did not complete treatment had generally more severe depressive and anxious symptoms and greater treatment resistance. No significant differences in response rates were observed across different TMS coils. ConclusionThe study demonstrated the effectiveness and tolerability of accelerated TMS for TRD in a real-world clinical setting.

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

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

High inductance magnetic-core coils have enhanced efficiency in inducing suprathreshold motor response in rats

Objective. Transcranial magnetic stimulation (TMS) coil design involves a tradeoff among multiple parameters, including magnetic flux density (B), inductance (L), induced electric (E) field, focality, penetration depth, coil heating, etc. Magnetic materials with high permeability have been suggested to enhance coil efficiency. However, the introduction of magnetic core invariably increases coil inductance compared to its air-core counterpart, which in turn weakens the E field. Our lab previously reported a rodent-specific TMS coil with silicon steel magnetic core, achieving 2 mm focality. This study aims to better understand the tradeoffs among B, L, and E in the presence of magnetic core. Approach. The magnetic core initially operates within the linear range, transitioning to the nonlinear range when it begins to saturate at high current levels and reverts to the linear range as coil current approaches zero; both linear and nonlinear analyses were performed. Linear analysis assumes a weak current condition when magnetic core is not saturated; a monophasic TMS circuit was employed for this purpose. Nonlinear analysis assumes a strong current condition with varying degrees of core saturation. Main results. Results reveal that, the secondary E field generated by the silicon steel core substantially changed the dynamics during TMS pulse. Linear and nonlinear analyses revealed that higher inductance coils produced stronger peak E fields and longer E field waveforms. On a macroscopic scale, the effects of these two factors on neuronal activation could be conceptually explained through a one-time-constant linear membrane model. Four coils with different B, L, and E characteristics were designed and constructed. Both E field mapping and experiments on awake rats confirmed that inductance could be much higher than previously anticipated, provided that magnetic material possesses a high saturation threshold. Significance. Our results highlight the novel potentials of magnetic core in TMS coil designs, especially for small animals.

Identifying Locations for Transcranial Magnetic Stimulation Coil Placement For Deep Brain Structures

Stimulation of deep brain structures with transcranial magnetic stimulation (TMS) is the premier mode of non-invasive brain stimulation (NIBS). Currently, there is little support for the application of TMS in modulating deeper brain structures. This study validates the use of TMS for a set of 8 deep brain structures shown to alleviate symptoms of certain conditions when stimulated. 200 sets of T1-weighted and T2-weighted MRIs were processed using the SimNIBS headreco pipeline. Then, 200 TMS optimization simulations were run for each brain structure, which generated 200 3D coordinates for each structure representing the best TMS coil placement locations on the scalp for stimulation. This data was analyzed using K-means and agglomerative clustering methods to find the overall best coil placement locations. Overall, this study validates the use of TMS to stimulate these brain structures and finds the optimal parameters for stimulation.

In-vivo verified anatomically aware deep learning for real-time electric field simulation

Objective. Transcranial magnetic stimulation (TMS) has emerged as a prominent non-invasive technique for modulating brain function and treating mental disorders. By generating a high-precision magnetically evoked electric field (E-field) using a TMS coil, it enables targeted stimulation of specific brain regions. However, current computational methods employed for E-field simulations necessitate extensive preprocessing and simulation time, limiting their fast applications in the determining the optimal coil placement. Approach. We present an attentional deep learning network to simulate E-fields. This network takes individual magnetic resonance images and coil configurations as inputs, firstly transforming the images into explicit brain tissues and subsequently generating the local E-field distribution near the target brain region. Main results. Relative to the previous deep-learning simulation method, the presented method reduced the mean relative error in simulated E-field strength of gray matter by 21.1%, and increased the correlation between regional E-field strengths and corresponding electrophysiological responses by 35.0% when applied into another dataset. In-vivo TMS experiments further revealed that the optimal coil placements derived from presented method exhibit comparable stimulation performance on motor evoked potentials to those obtained using computational methods. The simplified preprocessing and increased simulation efficiency result in a significant reduction in the overall time cost of traditional TMS coil placement optimization, from several hours to mere minutes. Significance. The precision and efficiency of presented simulation method hold promise for its application in determining individualized coil placements in clinical practice, paving the way for personalized TMS treatments.

Evoked EEG Responses to TMS Targeting Regions Outside the Primary Motor Cortex and Their Test–Retest Reliability

Transcranial magnetic stimulation (TMS)–evoked electroencephalography (EEG) potentials (TEPs) provide unique insights into cortical excitability and connectivity. However, confounding EEG signals from auditory and somatosensory co-stimulation complicate TEP interpretation. Our optimized sham procedure established with TMS of primary motor cortex (Gordon in JAMA 245:118708, 2021) differentiates direct cortical EEG responses to TMS from those caused by peripheral sensory inputs. Using this approach, this study aimed to investigate TEPs and their test–retest reliability when targeting regions outside the primary motor cortex, specifically the left angular gyrus, supplementary motor area, and medial prefrontal cortex. We conducted three identical TMS–EEG sessions one week apart involving 24 healthy participants. In each session, we targeted the three areas separately using a figure-of-eight TMS coil for active TMS, while a second coil away from the head produced auditory input for sham TMS. Masking noise and electric scalp stimulation were applied in both conditions to achieve matched EEG responses to peripheral sensory inputs. High test–retest reliability was observed in both conditions. However, reliability declined for the ‘cleaned’ TEPs, resulting from the subtraction of evoked EEG response to the sham TMS from those to the active, particularly for latencies > 100 ms following the TMS pulse. Significant EEG differences were found between active and sham TMS at latencies < 90 ms for all targeted areas, exhibiting distinct spatiotemporal characteristics specific to each target. In conclusion, our optimized sham procedure effectively reveals EEG responses to direct cortical activation by TMS in brain areas outside primary motor cortex. Moreover, we demonstrate the impact of peripheral sensory inputs on test–retest reliability of TMS-EEG responses.

EEG synchronized left prefrontal transcranial magnetic stimulation (TMS) for treatment resistant depression is feasible and produces an entrainment dependent clinical response: A randomized controlled double blind clinical trial

BackgroundSynchronizing a TMS pulse with a person's underlying EEG rhythm can modify the brain's response. It is unclear if synchronizing rTMS trains might boost the antidepressant effect of TMS. In this first-in-human trial, we demonstrated that a single TMS pulse over the prefrontal cortex produces larger effects in the anterior cingulate depending on when it is fired relative to the individual's EEG alpha phase. Objective/hypothesesWe had three hypotheses. 1) It is feasible to synchronize repetitive TMS (rTMS) delivery to a person's preferred prefrontal alpha phase in each train of every session during a 30-visit TMS depression treatment course. 2) EEG-synchronized rTMS would produce progressive entrainment greater than unsynchronized (UNSYNC) rTMS. And 3) SYNC TMS would have better antidepressant effects than UNSYNC (remission, final Hamilton Depression Rating <10). MethodsWe enrolled (n = 34) and treated (n = 28) adults with treatment resistant depression (TRD) and randomized them to receive six weeks (30 treatments) of left prefrontal rTMS at their individual alpha frequency (IAF) (range 6–13 Hz). Prior to starting the clinical trial, all patients had an interleaved fMRI-EEG-TMS (fET) scan to determine which phase of their alpha rhythm would produce the largest BOLD response in their dorsal anterior cingulate. Our clinical EEG-rTMS system then delivered the first TMS pulse in each train time-locked to this patient-specific ‘preferred phase’ of each patient's left prefrontal alpha oscillation. We randomized patients (1:1) to SYNC or UNSYNC, and all were treated at their IAF. Only the SYNC patients had the first pulse of each train for all sessions synchronized to their individualized preferred alpha phase (75 trains/session ×30 sessions, 2250 synchronizations per patient over six weeks). The UNSYNC group used a random firing with respect to the alpha wave. All other TMS parameters were balanced between the two groups.The system interfaced with a MagStim Horizon air-cooled Fig. 8 TMS coil. All patients were treated at their IAF, coil in the F3 position, 120 % MT, frequency 6–13 Hz, 40 pulses per train, average 15-s inter-train interval, 3000 pulses per session. All patients, raters, and treaters were blinded. ResultsIn the intent to treat (ITT) sample, both groups had significant clinical improvement from baseline with no significant between-group differences, with the USYNC group having mathematically more remitters but fewer responders. (ITT -15 SYNC; 13 UNSYNC, response 5 (33 %), 1 (7 %), remission 2 (13 %), 6 (46 %). The same was true with the completer sample - 12 SYNC; 12 UNSYNC, response 4, 4 (both 30 %), remission 2 (17 %), 3 (25 %)). The clinical EEG phase synchronization system performed well with no failures. The average treatment session was approximately 90 min, with 30 min for placing the EEG cap and the actual TMS treatment for 45 min (which included gathering 10 min of resting EEG). Four subjects (1 SYNC) withdrew before six weeks of treatment. All 24 completer patients were treated for six weeks despite the trial occurring during the COVID pandemic. SYNC patients exhibited increased post-stimulation EEG entrainment over the six weeks. A detailed secondary analysis of entrainment data in the SYNC group showed that responders and non-responders in this group could be cleanly separated based on the total number of sessions with entrainment and the session-to-session precision of the entrained phase. For the SYNC group only, depression improvement was greater when more sessions were entrained at similar phases. ConclusionsSynchronizing prefrontal TMS with a patient's prefrontal alpha frequency in a blinded clinical trial is possible and produces progressive EEG entrainment in synchronized patients only. There was no difference in overall clinical response in this small clinical trial. A secondary analysis showed that the consistency of the entrained phase across sessions was significantly associated with response outcome only in the SYNC group. These effects may not simply be due to how the stimulation is delivered but also whether the patient's brain can reliably entrain to a precise phase. EEG-synchronized clinical delivery of TMS is feasible and requires further study to determine the best method for determining the phase for synchronization.

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.

Investigating the electric field distribution in the human brain model induced by a high focality transcranial magnetic coil

Transcranial magnetic stimulation (TMS) is a noninvasive neuromodulation technique for treating various neurological disorders. The geometry of the TMS coil determines the focality, stimulation field strength, and stimulation depth of the induced electric field. In this paper, we introduce a novel coil, named the eccentric folding coil (EFC). We used Sim4Life, a three-dimensional human tissue medical electromagnetic simulation software, and the brain models of the subjects from the population head model repository to conduct finite element simulations of the eccentric folding coil, circular coil, and figure-eight coil, implying that the largest EFC has a focal area of 19.5 cm2 less than the smallest circular coil, and the EFC of any size has a smaller focal area than the figure-8 coil of the same size. Furthermore, we stimulated the model from three directions with the coil and measured the electric field responses of the model, confirming that stimulation varied in different directions. Additionally, we applied EFC to four representative human models and found that the electric field in different subjects’ brains differed by 3.03 mm in stimulation depth and 12.9 cm2 in focal area, suggesting that personalized human head modeling and electromagnetic analysis are essential for TMS treatment. In the future, we will explore using different types of TMS devices for patients with different conditions to achieve more precise and customized treatment.