Site- and frequency-specific enhancement of visual search performance with online individual alpha frequency (IAF) repetitive transcranial magnetic stimulation (rTMS) to the inferior frontal junction.

In this study, repetitive transcranial magnetic stimulation was applied to either the right inferior frontal junction or the right inferior parietal cortex during a difficult aerial reconnaissance search task to test its capacity to improve search performance. Two stimulation strategies previously found to enhance cognitive performance were tested: The first is called "addition by subtraction," and the second condition utilizes a direct excitatory approach by applying brief trains of high-frequency repetitive transcranial magnetic stimulation immediately before task trials. In a within-subjects design, participants were given active or sham repetitive transcranial magnetic stimulation at either 1 Hz or at 1 Hz above their individual peak alpha frequency (IAF + 1, mean 11.5 Hz), delivered to either the right inferior frontal junction or the right inferior parietal cortex, both defined with individualized peak functional magnetic resonance imaging (fMRI) activation obtained during the visual search task. Results indicated that among the 13 participants who completed the protocol, only active IAF + 1 stimulation to inferior frontal junction resulted in significant speeding of reaction time compared to sham. This site- and frequency-specific enhancement of performance with IAF + 1 repetitive transcranial magnetic stimulation applied immediately prior to task trials provides evidence for the involvement of inferior frontal junction in guiding difficult visual search, and more generally for the use of online repetitive transcranial magnetic stimulation directed at specific functional networks to enhance visual search performance.

Multimodal smoking cessation treatment combining repetitive transcranial magnetic stimulation, cognitive behavioral therapy, and nicotine replacement in veterans with posttraumatic stress disorder: A feasibility randomized controlled trial protocol.

Tobacco-related deaths remain the leading cause of preventable death in the United States. Veterans suffering from posttraumatic stress disorder (PTSD)-about 11% of those receiving care from the Department of Veterans Affairs (VA)-have triple the risk of developing tobacco use disorder (TUD). The most efficacious strategies being used at the VA for smoking cessation only result in a 23% abstinence rate, and veterans with PTSD only achieve a 4.5% abstinence rate. Therefore, there is a critical need to develop more effective treatments for smoking cessation. Recent studies suggest the insula is integrally involved in the neurocircuitry of TUD. Thus, we propose a feasibility phase II randomized controlled trial (RCT) to study a form of repetitive transcranial magnetic stimulation (rTMS) called intermittent theta burst stimulation (iTBS). iTBS has the advantage of allowing for a patterned form of stimulation delivery that we will administer at 90% of the subject's resting motor threshold (rMT) applied over a region in the right post-central gyrus most functionally connected to the right posterior insula. We hypothesize that by increasing functional connectivity between the right post-central gyrus and the right posterior insula, withdrawal symptoms and short-term smoking cessation outcomes will improve. Fifty eligible veterans with comorbid TUD and PTSD will be randomly assigned to active-iTBS + cognitive behavioral therapy (CBT) + nicotine replacement therapy (NRT) (n = 25) or sham-iTBS + CBT + NRT (n = 25). The primary outcome, feasibility, will be determined by achieving a recruitment of 50 participants and retention rate of 80%. The success of iTBS will be evaluated through self-reported nicotine use, cravings, withdrawal symptoms, and abstinence following quit date (confirmed by bioverification) along with evaluation for target engagement through neuroimaging changes, specifically connectivity differences between the insula and other regions of interest.

Electroconvulsive therapy modulates loudness dependence of auditory evoked potentials: a pilot MEG study.

Introduction: Electroconvulsive therapy (ECT) remains a critical intervention for treatment-resistant depression (MDD), yet its neurobiological underpinnings are not fully understood. This pilot study aims to investigate changes in loudness dependence of auditory evoked potentials (LDAEP), a proposed biomarker of serotonergic activity, in patients undergoing ECT. Methods: High-resolution magnetoencephalography (MEG) was utilized to measure LDAEP in nine depressed patients receiving right unilateral ECT. We hypothesized that ECT would reduce the LDAEP slope, reflecting enhanced serotonergic neurotransmission. Depression severity and cognitive performance were assessed using the 24-item Hamilton Depression Rating Scale (HDRS24) and the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), respectively. Results: Contrary to our hypothesis, findings indicated a significant increase in LDAEP post-ECT (t 8 = 3.17, p = .013). The increase in LDAEP was not associated with changes in depression severity or cognitive performance. Discussion: The observed increase in LDAEP suggests a more complex interaction between ECT and neurobiological systems, rather than a direct reflection of serotonergic neurotransmission. Potential mechanisms for this increase include ECT's impact on serotonergic, dopaminergic, glutamatergic, and GABAergic receptor activity, neuroplasticity involving brain-derived neurotrophic factor (BDNF), and inflammatory modulators such as TNF-α. Our results highlight the multifaceted effects of ECT on brain function, necessitating further research to elucidate these interactions.

Computational Models of High-Definition Electroconvulsive Therapy for Focal or Multitargeting Treatment.

ABSTRACT: Attempts to dissociate electroconvulsive therapy (ECT) therapeutic efficacy from cognitive side effects of ECT include modifying electrode placement, but traditional electrode placements employing 2 large electrodes are inherently nonfocal, limiting the ability to selectively engage targets associated with clinical benefit while avoiding nontargets associated with adverse side effects. Limited focality represents a technical limitation of conventional ECT, and there is growing evidence that the spatial distribution of the ECT electric fields induced in the brain drives efficacy and side effects. Computational models can be used to predict brain current flow patterns for existing and novel ECT montages. Using finite element method simulations (under quasi-static, nonadaptive assumptions, 800-mA total current), the electric fields generated in the superficial cortex and subcortical structures were predicted for the following traditional ECT montages (bilateral temporal, bifrontal, right unilateral) and experimental montages (focal electrically administered seizure therapy, lateralized high-definition [HD]-ECT, unilateral 4 × 1-ring HD-ECT, bilateral 4 × 1-ring HD-ECT, and a multipolar HD-ECT). Peak brain current density in regions of interest was quantified. Conventional montages (bilateral bifrontal, right unilateral) each produce distinct but diffuse and deep current flow. Focal electrically administered seizure therapy and lateralized HD-ECT produce unique, lateralized current flow, also impacting specific deep regions. A 4 × 1-ring HD-ECT restricts current flow to 1 (unilateral) or 2 (bilateral) cortical regions. Multipolar HD-ECT shows optimization to a specific target set. Future clinical trials are needed to determine whether enhanced control over current distribution is achieved with these experimental montages, and the resultant seizures, improve the risk/benefit ratio of ECT.

Ultra-high frequency repetitive TMS at subthreshold intensity induces suprathreshold motor response via temporal summation.

Objective.The transcranial magnetic stimulation (TMS) coil induces an electric field that diminishes rapidly upon entering the brain. This presents a challenge in achieving focal stimulation of a deep brain structure. Neuronal elements, including axons, dendrites, and cell bodies, exhibit specific time constants. When exposed to repetitive TMS pulses at a high frequency, there is a cumulative effect on neuronal membrane potentials, resulting in temporal summation. This study aims to determine whether TMS pulse train at high-frequency and subthreshold intensity could induce a suprathreshold response.Approach.As a proof of concept, we developed a TMS machine in-house that could consistently output pulses up to 250 Hz, and performed experiments on 22 awake rats to test whether temporal summation was detectable under pulse trains at 100, 166, or 250 Hz.Main results.Results revealed that TMS pulses at 55% maximum stimulator output (MSO, peak dI/dt= 68.5 A/µs at 100% MSO, pulse width = 48µs) did not induce motor responses with either single pulses or pulse trains. Similarly, a single TMS pulse at 65% MSO failed to evoke a motor response in rats; however, a train of TMS pulses at frequencies of 166 and 250 Hz, but not at 100 Hz, successfully triggered motor responses and MEP signals, suggesting a temporal summation effect dependent on both pulse intensities and pulse train frequencies.Significance.We propose that the temporal summation effect can be leveraged to design the next-generation focal TMS system: by sequentially driving multiple coils at high-frequency and subthreshold intensity, areas with the most significant overlapping E-fields undergo maximal temporal summation effects, resulting in a suprathreshold response.

Electroconvulsive Therapy Modulates Loudness Dependence of Auditory Evoked Potentials: A Pilot MEG Study.

Electroconvulsive therapy (ECT) remains a critical intervention for treatment-resistant depression (MDD), yet its neurobiological underpinnings are not fully understood. This pilot study utilizes high-resolution magnetoencephalography (MEG) in nine depressed patients receiving right unilateral ECT, to investigate the changes in loudness dependence of auditory evoked potentials (LDAEP), a proposed biomarker of serotonergic activity, following ECT. We hypothesized that ECT would reduce the LDAEP slope, reflecting enhanced serotonergic neurotransmission. Contrary to this, our findings indicated a significant increase in LDAEP post-ECT ( t 8 = 3.17, p = .013). The increase in LDAEP was not associated with changes in depression severity or cognitive performance, as assessed by the Hamilton Depression Rating Scale (HAMD-24) and Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). We discussed potential mechanisms for the observed increase, including ECT's impact on serotonergic, dopaminergic, glutamatergic, and GABAergic receptor activity, neuroplasticity involving brain-derived neurotrophic factor (BDNF), and inflammation modulators such as TNF- alpha . Our results suggest a complex interaction between ECT and these neurobiological systems, rather than a direct reflection of serotonergic neurotransmission.

Lessons learned from an fMRI-guided rTMS study on performance in a numerical Stroop task.

The Stroop task is a well-established tool to investigate the influence of competing visual categories on decision making. Neuroimaging as well as rTMS studies have demonstrated the involvement of parietal structures, particularly the intraparietal sulcus (IPS), in this task. Given its reliability, the numerical Stroop task was used to compare the effects of different TMS targeting approaches by Sack and colleagues (Sack AT 2009), who elegantly demonstrated the superiority of individualized fMRI targeting. We performed the present study to test whether fMRI-guided rTMS effects on numerical Stroop task performance could still be observed while using more advanced techniques that have emerged in the last decade (e.g., electrical sham, robotic coil holder system, etc.). To do so we used a traditional reaction time analysis and we performed, post-hoc, a more advanced comprehensive drift diffusion modeling approach. Fifteen participants performed the numerical Stroop task while active or sham 10 Hz rTMS was applied over the region of the right intraparietal sulcus (IPS) showing the strongest functional activation in the Incongruent > Congruent contrast. This target was determined based on individualized fMRI data collected during a separate session. Contrary to our assumption, the classical reaction time analysis did not show any superiority of active rTMS over sham, probably due to confounds such as potential cumulative rTMS effects, and the effect of practice. However, the modeling approach revealed a robust effect of rTMS on the drift rate variable, suggesting differential processing of congruent and incongruent properties in perceptual decision-making, and more generally, illustrating that more advanced computational analysis of performance can elucidate the effects of rTMS on the brain where simpler methods may not.

Intermittent theta-burst stimulation to the right dorsolateral prefrontal cortex may increase potentiated startle in healthy individuals.

Repetitive transcranial magnetic stimulation (rTMS) treatment protocols targeting the right dlPFC have been effective in reducing anxiety symptoms comorbid with depression. However, the mechanism behind these effects is unclear. Further, it is unclear whether these results generalize to non-depressed individuals. We conducted a series of studies aimed at understanding the link between anxiety potentiated startle and the right dlPFC, following a previous study suggesting that continuous theta burst stimulation (cTBS) to the right dlPFC can make people more anxious. Based on these results we hypothesized that intermittent TBS (iTBS), which is thought to have opposing effects on plasticity, may reduce anxiety when targeted at the same right dlPFC region. In this double-blinded, cross-over design, 28 healthy subjects underwent 12 study visits over a 4-week period. During each of their 2 stimulation weeks, they received four 600 pulse iTBS sessions (2/day), with a post-stimulation testing session occurring 24 h following the final iTBS session. One week they received active stimulation, one week they received sham. Stimulation weeks were separated by a 1-week washout period and the order of active/sham delivery was counterbalanced across subjects. During the testing session, we induced anxiety using the threat of unpredictable shock and measured anxiety potentiated startle. Contrary to our initial hypothesis, subjects showed increased startle reactivity following active compared to sham stimulation. These results replicate work from our two previous trials suggesting that TMS to the right dlPFC increases anxiety potentiated startle, independent of both the pattern of stimulation and the timing of the post stimulation measure. Although these results confirm a mechanistic link between right dlPFC excitability and startle, capitalizing upon this link for the benefit of patients will require future exploration.

Bayesian Optimization of Neurostimulation (BOONStim).

BACKGROUND: Transcranial magnetic stimulation (TMS) treatment response is influenced by individual variability in brain structure and function. Sophisticated, user-friendly approaches, incorporating both established functional magnetic resonance imaging (fMRI) and TMS simulation tools, to identify TMS targets are needed. OBJECTIVE: The current study presents the development and validation of the Bayesian Optimization of Neuro-Stimulation (BOONStim) pipeline. METHODS: BOONStim uses Bayesian optimization for individualized TMS targeting, automating interoperability between surface-based fMRI analytic tools and TMS electric field modeling. Bayesian optimization performance was evaluated in a sample dataset (N=10) using standard circular and functional connectivity-defined targets, and compared to grid optimization. RESULTS: Bayesian optimization converged to similar levels of total electric field stimulation across targets in under 30 iterations, converging within a 5% error of the maxima detected by grid optimization, and requiring less time. CONCLUSIONS: BOONStim is a scalable and configurable user-friendly pipeline for individualized TMS targeting with quick turnaround.

Enabling Electric Field Modeling of Microscopically Realistic Brain.

Across all domains of brain stimulation (neuromodulation), conventional analysis of neuron activation involves two discrete steps: i) prediction of macroscopic electric field, ignoring presence of cells and; ii) prediction of cell activation from tissue electric fields. The first step assumes that current flow is not distorted by the dense tortuous network of cell structures. The deficiencies of this assumption have long been recognized, but - except for trivial geometries - ignored, because it presented intractable computation hurdles. This study introduces a novel approach for analyzing electric fields within a microscopically realistic brain volume. Our pipeline overcomes the technical intractability that prevented such analysis while also showing significant implications for brain stimulation. Contrary to the standard finite element method (FEM), we suggest using a nested iterative boundary element method (BEM) coupled with the fast multipole method (FMM). This approach allows for solving problems with multiple length scales more efficiently. A target application is a subvolume of the L2/3 P36 mouse primary visual cortex containing approximately 400 detailed densely packed neuronal cells at a resolution of 100 nm, which is obtained from scanning electron microscopy data. Our immediate result is a reduction of the stimulation field strength necessary for neuron activation by a factor of 0.85-0.55 (by 15%-45%) as compared to macroscopic predictions. This is in line with modern experimental data stating that existing macroscopic theories substantially overestimate electric field levels necessary for brain stimulation.

Electric Field Characteristics of Rotating Permanent Magnet Stimulation.

Neurostimulation devices that use rotating permanent magnets are being explored for their potential therapeutic benefits in patients with psychiatric and neurological disorders. This study aims to characterize the electric field (E-field) for ten configurations of rotating magnets using finite element analysis and phantom measurements. Various configurations were modeled, including single or multiple magnets, and bipolar or multipolar magnets, rotated at 10, 13.3, and 350 revolutions per second (rps). E-field strengths were also measured using a hollow sphere (r=9.2 cm) filled with a 0.9% sodium chloride solution and with a dipole probe. The E-field spatial distribution is determined by the magnets' dimensions, number of poles, direction of the magnetization, and axis of rotation, while the E-field strength is determined by the magnets' rotational frequency and magnetic field strength. The induced E-field strength on the surface of the head ranged between 0.0092 and 0.52 V/m. In the range of rotational frequencies applied, the induced E-field strengths were approximately an order or two of magnitude lower than those delivered by conventional transcranial magnetic stimulation. The impact of rotational frequency on E-field strength represents a confound in clinical trials that seek to tailor rotational frequency to individual neural oscillations. This factor could explain some of the variability observed in clinical trial outcomes.

Design and methodology for a proof of mechanism study of individualized neuronavigated continuous Theta burst stimulation for auditory processing in adolescents with autism spectrum disorder.

It has been suggested that aberrant excitation/inhibition (E/I) balance and dysfunctional structure and function of relevant brain networks may underlie the symptoms of autism spectrum disorder (ASD). However, the nomological network linking these constructs to quantifiable measures and mechanistically relating these constructs to behavioral symptoms of ASD is lacking. Herein we describe a within-subject, controlled, proof-of-mechanism study investigating the pathophysiology of auditory/language processing in adolescents with ASD. We utilize neurophysiological and neuroimaging techniques including magnetic resonance spectroscopy (MRS), diffusion-weighted imaging (DWI), functional magnetic resonance imaging (fMRI), and magnetoencephalography (MEG) metrics of language network structure and function. Additionally, we apply a single, individually targeted session of continuous theta burst stimulation (cTBS) as an experimental probe of the impact of perturbation of the system on these neurophysiological and neuroimaging outcomes. MRS, fMRI, and MEG measures are evaluated at baseline and immediately prior to and following cTBS over the posterior superior temporal cortex (pSTC), a region involved in auditory and language processing deficits in ASD. Also, behavioral measures of ASD and language processing and DWI measures of auditory/language network structures are obtained at baseline to characterize the relationship between the neuroimaging and neurophysiological measures and baseline symptom presentation. We hypothesize that local gamma-aminobutyric acid (GABA) and glutamate concentrations (measured with MRS), and structural and functional activity and network connectivity (measured with DWI and fMRI), will significantly predict MEG indices of auditory/language processing and behavioral deficits in ASD. Furthermore, a single session of cTBS over left pSTC is hypothesized to lead to significant, acute changes in local glutamate and GABA concentration, functional activity and network connectivity, and MEG indices of auditory/language processing. We have completed the pilot phase of the study (n=20 Healthy Volunteer adults) and have begun enrollment for the main phase with adolescents with ASD (n=86; age 14-17). If successful, this study will establish a nomological network linking local E/I balance measures to functional and structural connectivity within relevant brain networks, ultimately connecting them to ASD symptoms. Furthermore, this study will inform future therapeutic trials using cTBS to treat the symptoms of ASD.

An adaptive h-refinement method for the boundary element fast multipole method for quasi-static electromagnetic modeling.

Objective.In our recent work pertinent to modeling of brain stimulation and neurophysiological recordings, substantial modeling errors in the computed electric field and potential have sometimes been observed for standard multi-compartment head models. The goal of this study is to quantify those errors and, further, eliminate them through an adaptive mesh refinement (AMR) algorithm. The study concentrates on transcranial magnetic stimulation (TMS), transcranial electrical stimulation (TES), and electroencephalography (EEG) forward problems.Approach.We propose, describe, and systematically investigate an AMR method using the boundary element method with fast multipole acceleration (BEM-FMM) as the base numerical solver. The goal is to efficiently allocate additional unknowns to critical areas of the model, where they will best improve solution accuracy. The implemented AMR method's accuracy improvement is measured on head models constructed from 16 Human Connectome Project subjects under problem classes of TES, TMS, and EEG. Errors are computed between three solutions: an initial non-adaptive solution, a solution found after applying AMR with a conservative refinement rate, and a 'silver-standard' solution found by subsequent 4:1 global refinement of the adaptively-refined model.Main results.Excellent agreement is shown between the adaptively-refined and silver-standard solutions for standard head models. AMR is found to be vital for accurate modeling of TES and EEG forward problems for standard models: an increase of less than 25% (on average) in number of mesh elements for these problems, efficiently allocated by AMR, exposes electric field/potential errors exceeding 60% (on average) in the solution for the unrefined models.Significance.This error has especially important implications for TES dosing prediction-where the stimulation strength plays a central role-and for EEG lead fields. Though the specific form of the AMR method described here is implemented for the BEM-FMM, we expect that AMR is applicable and even required for accurate electromagnetic simulations by other numerical modeling packages as well.

Electric field characteristics of rotating permanent magnet stimulation.

Neurostimulation devices that use rotating permanent magnets are being explored for their potential therapeutic benefits in patients with psychiatric and neurological disorders. This study aims to characterize the electric field (E-field) for ten configurations of rotating magnets using finite element analysis and phantom measurements. Various configurations were modeled, including single or multiple magnets, bipolar or multipolar magnets, rotated at 10, 13.3, and 400 Hz. E-field strengths were also measured using a hollow sphere ( r = 9.2 cm) filled with a 0.9% sodium chloride solution and with a dipole probe. The E-field spatial distribution is determined by the magnets' dimensions, number of poles, direction of the magnetization, and axis of rotation, while the E-field strength is determined by the magnets' rotational frequency and magnetic field strength. The induced E-field strength on the surface of the head ranged between 0.0092 and 0.59 V/m. At the range of rotational frequencies applied, the induced E-field strengths were approximately an order or two of magnitude lower than those delivered by conventional transcranial magnetic stimulation. The impact of rotational frequency on E-field strength represents a previously unrecognized confound in clinical trials that seek to personalize stimulation frequency to individual neural oscillations and may represent a mechanism to explain some clinical trial results.

Amplitude-determined seizure-threshold, electric field modeling, and electroconvulsive therapy antidepressant and cognitive outcomes.

Electroconvulsive therapy (ECT) pulse amplitude, which dictates the induced electric field (E-field) magnitude in the brain, is presently fixed at 800 or 900 milliamperes (mA) without clinical or scientific rationale. We have previously demonstrated that increased E-field strength improves ECT's antidepressant effect but worsens cognitive outcomes. Amplitude-determined seizure titration may reduce the E-field variability relative to fixed amplitude ECT. In this investigation, we assessed the relationships among amplitude-determined seizure-threshold (STa), E-field magnitude, and clinical outcomes in older adults (age range 50 to 80 years) with depression. Subjects received brain imaging, depression assessment, and neuropsychological assessment pre-, mid-, and post-ECT. STa was determined during the first treatment with a Soterix Medical 4×1 High Definition ECT Multi-channel Stimulation Interface (Investigation Device Exemption: G200123). Subsequent treatments were completed with right unilateral electrode placement (RUL) and 800 mA. We calculated Ebrain defined as the 90th percentile of E-field magnitude in the whole brain for RUL electrode placement. Twenty-nine subjects were included in the final analyses. Ebrain per unit electrode current, Ebrain/I, was associated with STa. STa was associated with antidepressant outcomes at the mid-ECT assessment and bitemporal electrode placement switch. Ebrain/I was associated with changes in category fluency with a large effect size. The relationship between STa and Ebrain/I extends work from preclinical models and provides a validation step for ECT E-field modeling. ECT with individualized amplitude based on E-field modeling or STa has the potential to enhance neuroscience-based ECT parameter selection and improve clinical outcomes.

The impact of body mass index on the clinical features of bipolar disorder: A STEP-BD study.

INTRODUCTION: The effects of body mass index (BMI) on the core symptoms of bipolar disorder (BD) and its implications for disease trajectory are largely unexplored. OBJECTIVE: To examine whether BMI impacted hospitalization rate, medical and psychiatric comorbidities, and core symptom domains such as depression and suicidality in BD. METHODS: Participants (15 years and older) were 2790 BD outpatients enrolled in the longitudinal STEP-BD study; all met DSM-IV criteria for BD-I, BD-II, cyclothymia, BD NOS, or schizoaffective disorder, bipolar subtype. BMI, demographic information, psychiatric and medical comorbidities, and other clinical variables such as bipolarity index, history of electroconvulsive therapy (ECT), and history of suicide attempts were collected at baseline. Longitudinal changes in Montgomery-Åsberg Depression Rating Scale (MADRS) score, Young Mania Rating Scale (YMRS) score, and hospitalizations during the study were also assessed. Depending on the variable of interest, odds-ratios, regression analyses, factor analyses, and graph analyses were applied. RESULTS: A robust increase in psychiatric and medical comorbidities was observed, particularly for baseline BMIs >35. A significant relationship was noted between higher BMI and history of suicide attempts, and individuals with BMIs >40 had the highest prevalence of suicide attempts. Obese and overweight individuals had a higher bipolarity index (a questionnaire measuring disease severity) and were more likely to have received ECT. Higher BMIs correlated with worsening trajectory of core depression symptoms and with worsening lassitude and inability to feel. CONCLUSIONS: In BD participants, elevated BMI was associated with worsening clinical features, including higher rates of suicidality, comorbidities, and core depression symptoms.

Electric Field Modeling in Personalizing Transcranial Magnetic Stimulation Interventions.

The modeling of transcranial magnetic stimulation (TMS)-induced electric fields (E-fields) is a versatile technique for evaluating and refining brain targeting and dosing strategies, while also providing insights into dose-response relationships in the brain. This review outlines the methodologies employed to derive E-field estimations, covering TMS physics, modeling assumptions, and aspects of subject-specific head tissue and coil modeling. We also summarize various numerical methods for solving the E-field and their suitability for various applications. Modeling methodologies have been optimized to efficiently execute numerous TMS simulations across diverse scalp coil configurations, facilitating the identification of optimal setups or rapid cortical E-field visualization for specific brain targets. These brain targets are extrapolated from neurophysiological measurements and neuroimaging, enabling precise and individualized E-field dosing in experimental and clinical applications. This necessitates the quantification of E-field estimates using metrics that enable the comparison of brain target engagement, functional localization, and TMS intensity adjustments across subjects. The integration of E-field modeling with empirical data has the potential to uncover pivotal insights into the aspects of E-fields responsible for stimulating and modulating brain function and states, enhancing behavioral task performance, and impacting the clinical outcomes of personalized TMS interventions.

The Efficacy of Transcranial Magnetic Stimulation in the Treatment of Obsessive-Compulsive Disorder: An Umbrella Review of Meta-Analyses.

BACKGROUND: Repetitive transcranial magnetic stimulation (rTMS) has been increasingly used for treating obsessive-compulsive disorder (OCD). Although several meta-analyses have explored its effectiveness and safety, there is no umbrella review specifically focused on rTMS for OCD. This umbrella review followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and analyzed relevant meta-analyses on rTMS for OCD. METHODS: Twenty-three articles were identified from PubMed, and after screening, 12 meta-analyses were included in the review. The studies analyzed in the meta-analyses ranged from 10 to 27, with total participants ranging from 282 to 791. The most commonly studied regions were the dorsolateral prefrontal cortex (DLPFC), supplementary motor area (SMA), and orbito-frontal cortex (OFC). RESULT: The majority of the meta-analyses consistently supported the effectiveness of rTMS in reducing OCD symptoms when applied to the DLPFC and SMA. Encouraging results were also observed when targeting the medial prefrontal cortex (mPFC) and anterior cingulate cortex (ACC) through deep transcranial magnetic stimulation (dTMS). However, there was a high level of heterogeneity in the findings of nine out of 12 meta-analyses. CONCLUSION: In conclusion, existing evidence suggests that rTMS targeting the DLPFC and SMA consistently reduces OCD symptoms, but targeting the mPFC and ACC through dTMS shows variable results. However, the high heterogeneity in the study findings indicates a need for further research and standardization in the field.