Focality of the Induced E-Field Is a Contributing Factor in the Choice of TMS Parameters: Evidence from a 3D Computational Model of the Human Brain

ViTab Transformer Framework for Predicting Induced Electric Field and Focality in Transcranial Magnetic Stimulation

Transcranial magnetic stimulation is an electromagnetic induction-based non-invasive therapeutic technique for neurological diseases. For finding new clinical applications and enhancing the efficacy of TMS in existing neurological disorders, the current study focuses on a deep learning-based prediction model as an alternative to time-consuming electromagnetic (EM) simulation software. The main bottleneck of the existing prediction models is to consider very few input parameters of a standard coil such as coil type and coil position for predicting an output of electric field value. To overcome this limitation, a transformer-based prediction model titled as ViTab transformer is developed in this work to predict electric field (E-max), focality or area of stmulation (S-half), and volume of stimulation (V-half) by considering several input parameters such as sources of MRI images, types of coils, coil position, rate of change of current, brain tissues conductivity, and coil distance from the scalp. The proposed framework consists of a vision and a tab transformer to handle both image and tabular-type data. The prediction performance of the offered model is evaluated in terms of coefficient determination, R2 score, for E-max, V-half, and S-half in the testing phase. The obtained result in terms of R2 score for E-max, V-half, and S-half are found 0.97, 0.87, and 0.90 respectively. The results indicate that the suggested ViTab transformer model can predict electric field as well as focality more accurately than the current state-of-the-art methods. The reduced computational time, as well as efficient prediction accuracy, resembles that ViTab transformer can assist the neuroscientist and neurosurgeon prior to providing superior TMS treatment in near future.

MNI2CPC: A probabilistic cortex-to-scalp mapping for non-invasive brain stimulation targeting

BACKGROUND

Synthesis of neural imaging information from many studies is valuable for identifying stable cortical targets for non-invasive brain stimulation (NIBS). Typically, these targets are specified in Montreal Neurological Institute (MNI) standard brain space. However, in practical NIBS applications, localizing MNI cortical targets often relies on the International 10-20 system or heuristic scalp approaches, which often lacks precision or applies only to specific targets.

OBJECTIVE/HYPOTHESIS

We aim to establish a probabilistic mapping from any cortical target in MNI space to continuous proportional coordinate (CPC) standard scalp space (MNI2CPC) and assess the performance of this mapping for NIBS targeting.

METHODS

The MNI2CPC mapping was calculated based on a large MRI dataset (n = 114). Its targeting error was evaluated via cross-individual validation using a leave-one-out approach, as well as through independent validation across race (n = 27) and across patient (n = 58) cohorts.

RESULTS

The cross-individual validation demonstrated targeting errors of 4.03 ± 0.69 mm on the scalp and 3.30 ± 0.59 mm in the cortex. For independent cohorts, targeting errors were 4.71 ± 0.81 mm (scalp) and 3.85 ± 0.64 mm (cortex) across race, and 4.66 ± 0.77 mm (scalp) and 3.77 ± 0.61 mm (cortex) across patient. We publish a free online tool to enable querying of the CPC coordinate for any given MNI cortical target. The resulting CPC coordinates enable rapid and accurate manual localization on the scalp in a user-friendly manner.

CONCLUSIONS

The MNI2CPC mapping developed in this study allows for manual localization of any MNI cortical target, which improves the accessibility and ease of application of NIBS in diverse settings.

Outcome measures for electric field modeling in tES and TMS: A systematic review and large-scale modeling study

BACKGROUND

Electric field (E-field) modeling is a potent tool to estimate the amount of transcranial magnetic and electrical stimulation (TMS and tES, respectively) that reaches the cortex and to address the variable behavioral effects observed in the field. However, outcome measures used to quantify E-fields vary considerably and a thorough comparison is missing.

OBJECTIVES

This two-part study aimed to examine the different outcome measures used to report on tES and TMS induced E-fields, including volume- and surface-level gray matter, region of interest (ROI), whole brain, geometrical, structural, and percentile-based approaches. The study aimed to guide future research in informed selection of appropriate outcome measures.

METHODS

Three electronic databases were searched for tES and/or TMS studies quantifying E-fields. The identified outcome measures were compared across volume- and surface-level E-field data in ten tES and TMS modalities targeting two common targets in 100 healthy individuals.

RESULTS

In the systematic review, we extracted 308 outcome measures from 202 studies that adopted either a gray matter volume-level (n = 197) or surface-level (n = 111) approach. Volume-level results focused on E-field magnitude, while surface-level data encompassed E-field magnitude (n = 64) and normal/tangential E-field components (n = 47). E-fields were extracted in ROIs, such as brain structures and shapes (spheres, hexahedra and cylinders), or the whole brain. Percentiles or mean values were mostly used to quantify E-fields. Our modeling study, which involved 1,000 E-field models and > 1,000,000 extracted E-field values, revealed that different outcome measures yielded distinct E-field values, analyzed different brain regions, and did not always exhibit strong correlations in the same within-subject E-field model.

CONCLUSIONS

Outcome measure selection significantly impacts the locations and intensities of extracted E-field data in both tES and TMS E-field models. The suitability of different outcome measures depends on the target region, TMS/tES modality, individual anatomy, the analyzed E-field component and the research question. To enhance the quality, rigor, and reproducibility in the E-field modeling domain, we suggest standard reporting practices across studies and provide four recommendations.

Template MRI scans reliably approximate individual and group-level tES and TMS electric fields induced in motor and prefrontal circuits

Background

Electric field (E-field) modeling is a valuable method of elucidating the cortical target engagement from transcranial magnetic stimulation (TMS) and transcranial electrical stimulation (tES), but it is typically dependent on individual MRI scans. In this study, we systematically tested whether E-field models in template MNI-152 and Ernie scans can reliably approximate group-level E-fields induced in N = 195 individuals across 5 diagnoses (healthy, alcohol use disorder, tobacco use disorder, anxiety, depression).

Methods

We computed 788 E-field models using the CHARM-SimNIBS 4.0.0 pipeline with 4 E-field models per participant (motor and prefrontal targets for TMS and tES). We additionally calculated permutation analyses to determine the point of stability of E-fields to assess whether the 152 brains represented in the MNI-152 template is sufficient.

Results

Group-level E-fields did not significantly differ between the individual vs. MNI-152 template and Ernie scans for any stimulation modality or location (p > 0.05). However, TMS-induced E-field magnitudes significantly varied by diagnosis; individuals with generalized anxiety had significantly higher prefrontal and motor E-field magnitudes than healthy controls and those with alcohol use disorder and depression (p < 0.001). The point of stability for group-level E-field magnitudes ranged from 42 (motor tES) to 52 participants (prefrontal TMS).

Conclusion

MNI-152 and Ernie models reliably estimate group-average TMS and tES-induced E-fields transdiagnostically. The MNI-152 template includes sufficient scans to control for interindividual anatomical differences (i.e., above the point of stability). Taken together, using the MNI-152 and Ernie brains to approximate group-level E-fields is a valid and reliable approach.

The Relation between Induced Electric Field and TMS-Evoked Potentials: A Deep TMS-EEG Study

Transcranial magnetic stimulation (TMS) in humans induces electric fields (E-fields, EF) that perturb and modulate the brain’s endogenous neuronal activity and result in the generation of TMS-evoked potentials (TEPs). The exact relation of the characteristics of the induced E-field and the intensity of the brains’ response, as measured by electroencephalography (EEG), is presently unclear. In this pilot study, conducted on three healthy subjects and two patients with generalized epilepsy (total: 3 males, 2 females, mean age of 26 years; healthy: 2 males, 1 female, mean age of 25.7 years; patients: 1 male, 1 female, mean age of 26.5 years), we investigated the temporal and spatial relations of the E-field, induced by single-pulse stimuli, and the brain’s response to TMS. Brain stimulation was performed with a deep TMS device (BrainsWay Ltd., Jerusalem, Israel) and an H7 coil placed over the central area. The induced EF was computed on personalized anatomical models of the subjects through magneto quasi-static simulations. We identified specific time instances and brain regions that exhibit high positive or negative associations of the E-field with brain activity. In addition, we identified significant correlations of the brain’s response intensity with the strength of the induced E-field and finally prove that TEPs are better correlated with E-field characteristics than with the stimulator’s output. These observations provide further insight in the relation between E-field and the ensuing cortical activation, validate in a clinically relevant manner the results of E-field modeling and reinforce the view that personalized approaches should be adopted in the field of non-invasive brain stimulation.

Exploring the spatial resolution of TMS-EEG coupling on the sensorimotor region

The use of TMS-EEG coupling as a neuroimaging tool for the functional exploration of the human brain recently gained strong interest. If this tool directly inherits the fine temporal resolution from EEG, its spatial counterpart remains unknown. In this study, we explored the spatial resolution of TMS-EEG coupling by evaluating the minimal distance between two stimulated cortical sites that would significantly evoke different response dynamics. TMS evoked responses were mapped on the sensorimotor region in twenty participants. The stimulation grid was composed of nine targets separated between 10 and 15 mm on average. The dynamical signatures of TMS evoked activity were extracted and compared between sites using both local and remote linear regression scores and spatial generalized mixed models. We found a significant effect of the distance between stimulated sites on their dynamical signatures, neighboring sites showing differentiable response dynamics. Besides, common dynamical signatures were also found between sites up to 25-30 mm from each other. This overlap in dynamical properties decreased with distance and was stronger between sites within the same Brodmann area. Our results suggest that the spatial resolution of TMS-EEG coupling might be at least as high as 10 mm. Furthermore, our results reveal an anisotropic spatial resolution that was higher across than within the same Brodmann areas, in accordance with the TMS induced E-field modeling. Common cytoarchitectonic leading to shared dynamical properties within the same Brodmann area could also explain this anisotropy. Overall, these findings suggest that TMS-EEG benefits from the spatial resolution of TMS, which makes it an accurate technique for meso-scale brain mapping.

Stimulation Parameters Used During Repetitive Transcranial Magnetic Stimulation for Motor Recovery and Corticospinal Excitability Modulation in SCI: A Scoping Review

There is a growing interest in non-invasive stimulation interventions as treatment strategies to improve functional outcomes and recovery after spinal cord injury (SCI). Repetitive transcranial magnetic stimulation (rTMS) is a neuromodulatory intervention which has the potential to reinforce the residual spinal and supraspinal pathways and induce plasticity. Recent reviews have highlighted the therapeutic potential and the beneficial effects of rTMS on motor function, spasticity, and corticospinal excitability modulation in SCI individuals. For this scoping review, we focus on the stimulation parameters used in 20 rTMS protocols. We extracted the rTMS parameters from 16 published rTMS studies involving SCI individuals and were able to infer preliminary associations between specific parameters and the effects observed. Future investigations will need to consider timing, intervention duration and dosage (in terms of number of sessions and number of pulses) that may depend on the stage, the level, and the severity of the injury. There is a need for more real vs. sham rTMS studies, reporting similar designs with sufficient information for replication, to achieve a significant level of evidence regarding the use of rTMS in SCI.

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

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

Fast acquisition of resting motor threshold with a stimulus-response curve - Possibility or hazard for transcranial magnetic stimulation applications?

Objective

Previous research has suggested that transcranial magnetic stimulation (TMS) related cortical excitability measures could be estimated quickly using stimulus-response curves with short interstimulus intervals (ISIs). Here we evaluated the resting motor threshold (rMT) estimated with these curves.

Methods

Stimulus-response curves were measured with three ISIs: 1.2-2 s, 2-3 s, and 3-4 s. Each curve was formed with 108 stimuli using stimulation intensities ranging from 0.75 to 1.25 times the rMT_guess, which was estimated based on motor evoked potential (MEP) amplitudes of three scout responses.

Results

The ISI did not affect the rMT estimated from the curves (F = 0.235, p = 0.683) or single-trial MEP amplitudes at the group level (F = 0.90, p = 0.405), but a significant subject by ISI interaction (F = 3.64; p < 0.001) was detected in MEP amplitudes. No trend was observed which ISI was most excitable, as it varied between subjects.

Conclusions

At the group level, the stimulus-response curves are unaffected by the short ISI. At the individual level, these curves are highly affected by the ISI.

Significance

Estimating rMT using stimulus-response curves with short ISIs impacts the rMT estimate and should be avoided in clinical and research TMS applications.