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

Direction of TIS envelope electric field: Perpendicular to the longitudinal axis of the hippocampus

BACKGROUND

Temporal Interference Stimulation (TIS) is a non-invasive approach to deep brain stimulation. However, most research has focused on the intensity of modulation, with limited attention given to the directional properties of the induced electric fields, despite their potential importance for precise stimulation.

NEW METHODS

A novel analytical framework was developed to analyze TIS-induced electric field directions using individual imaging data. For each voxel, the direction corresponding to the maximal modulation depth was calculated. The consistency of these directions within regions of interest (ROIs) and their alignment with the ROI principal axes, derived from principal component analysis (PCA), were assessed.

RESULTS

Simulations revealed complex spatial and temporal trajectories of the electric field at the voxel level. In the left putamen, the maximal modulation depth reached 0.241 ± 0.041 V/m, whereas in the target region, the left hippocampus, it was lower (0.15 ± 0.032 V/m). Notably, in the left hippocampus, the directions of maximal modulation depth were predominantly perpendicular to its longitudinal axis (84.547 ± 8.776°), reflecting structural specificity across its anterior, middle, and posterior regions.

COMPARISON WITH EXISTING METHODS

Unlike previous approaches, this study integrates directional analysis into TIS modeling, providing a foundation for precise stimulation by exploring structural alignment.

CONCLUSION

Our analysis revealed that the orientations of maximal modulation depth in the left hippocampus were perpendicular to its longitudinal axis under the current electrode configuration, but they shifted to parallel alignment when the electrode pairs were swapped. This directional specificity offers insights for optimizing TIS by aligning with structural features, presenting a potential strategy to enhance stimulation precision and broaden its clinical and research applications.

Optimizing TMS dosimetry: evaluating the effective electric field as a novel metric

Objective. This study introduces the effective electric field (Eeff) as a novel observable for transcranial magnetic stimulation (TMS) numerical dosimetry.Eeffrepresents the electric field component aligned with the local orientation of cortical and white matter (WM) neuronal elements. To assess the utility ofEeffas a predictive measure for TMS outcomes, we evaluated its correlation with TMS induced muscle responses and compared it against conventional observables, including the electric (E-)field magnitude, and its components normal and tangential to the cortical surface.Approach.Using a custom-made software for TMS dosimetry, theEeffis calculated combining TMS dosimetric results from an anisotropic head model with tractography data of gray and white matter (GM and WM). To test the hypothesis thatEeffhas a stronger correlation with muscle response, a proof-of-concept experiment was conducted. Seven TMS sessions, with different coil rotations, targeted the primary motor area of a healthy subject. Motor evoked potentials (MEPs) were recorded from the first dorsal interosseous muscle.Main results.TheEefftrend for the seven TMS coil rotations closely matched the measured MEP response, displaying an ascending pattern that peaked and then symmetrically declined. In contrast, theE-field magnitude and its components tangential (Etan) and normal (Enorm) to the cortical surface were less responsive to coil orientation changes.Eeffshowed a strong correlation with MEPs (r= 0.8), while the other observables had a weaker correlation (0.5 forEnormand below 0.2 forE-field magnitude andEtan).Significance.This study is the first to evaluateEeff, a novel component of the TMS inducedE-field. Derived using tractography data from both white and GM,Eeffinherently captures axonal organization and local orientation. By demonstrating its correlation with MEPs, this work introducesEeffas a promising observable for future TMS dosimetric studies, with the potential to improve the precision of TMS applications.

A review of algorithms and software for real-time electric field modeling techniques for transcranial magnetic stimulation

Transcranial magnetic stimulation (TMS) is a device-based neuromodulation technique increasingly used to treat brain diseases. Electric field (E-field) modeling is an important technique in several TMS clinical applications, including the precision stimulation of brain targets with accurate stimulation density for the treatment of mental disorders and the localization of brain function areas for neurosurgical planning. Classical methods for E-field modeling usually take a long computation time. Fast algorithms are usually developed with significantly lower spatial resolutions that reduce the prediction accuracy and limit their usage in real-time or near real-time TMS applications. This review paper discusses several modern algorithms for real-time or near real-time TMS E-field modeling and their advantages and limitations. The reviewed methods include techniques such as basis representation techniques and deep neural-network-based methods. This paper also provides a review of software tools that can integrate E-field modeling with navigated TMS, including a recent software for real-time navigated E-field mapping based on deep neural-network models.

Probing Our Built-in Calculator: A Systematic Narrative Review of Noninvasive Brain Stimulation Studies on Arithmetic Operation-Related Brain Areas

This systematic review presented a comprehensive survey of studies that applied transcranial magnetic stimulation and transcranial electrical stimulation to parietal and nonparietal areas to examine the neural basis of symbolic arithmetic processing. All findings were compiled with regard to the three assumptions of the triple-code model (TCM) of number processing. Thirty-seven eligible manuscripts were identified for review (33 with healthy participants and 4 with patients). Their results are broadly consistent with the first assumption of the TCM that intraparietal sulcus both hold a magnitude code and engage in operations requiring numerical manipulations such as subtraction. However, largely heterogeneous results conflicted with the second assumption of the TCM that the left angular gyrus subserves arithmetic fact retrieval, such as the retrieval of rote-learned multiplication results. Support is also limited for the third assumption of the TCM, namely, that the posterior superior parietal lobule engages in spatial operations on the mental number line. Furthermore, results from the stimulation of brain areas outside of those postulated by the TCM show that the bilateral supramarginal gyrus is involved in online calculation and retrieval, the left temporal cortex in retrieval, and the bilateral dorsolateral prefrontal cortex and cerebellum in online calculation of cognitively demanding arithmetic problems. The overall results indicate that multiple cortical areas subserve arithmetic skills.

How does the electric field induced by tDCS influence motor-related connectivity? Model-guided perspectives

Over the last decade, transcranial direct current stimulation (tDCS) has been applied not only to modulate local cortical activation, but also to address communication between functionally-related brain areas. Stimulation protocols based on simple two-electrode placements are being replaced by multi-electrode montages to target intra- and inter-hemispheric neural networks using multichannel/high definition paradigms.Objective. This study aims to investigate the characteristics of electric field (EF) patterns originated by tDCS experiments addressing changes in functional brain connectivity.Methods. A previous selection of tDCS experimental studies aiming to modulate motor-related connectivity in health and disease was conducted. Simulations of the EF induced in the cortex were then performed for each protocol selected. The EF magnitude and orientation are determined and analysed in motor-related cortical regions for five different head models to account for inter-subject variability. Functional connectivity outcomes obtained are qualitatively analysed at the light of the simulated EF and protocol characteristics, such as electrode position, number and stimulation dosing.Main findings. The EF magnitude and orientation predicted by computational models can be related with the ability of tDCS to modulate brain functional connectivity. Regional differences in EF distributions across subjects can inform electrode placements more susceptible to inter-subject variability in terms of brain connectivity-related outcomes.Significance. Neuronal facilitation/inhibition induced by tDCS fields may indirectly influence intra and inter-hemispheric connectivity by modulating neural components of motor-related networks. Optimization of tDCS using computational models is essential for adequate dosing delivery in specific networks related to clinically relevant connectivity outcomes.

Small effects of electric field on motor cortical excitability following anodal tDCS

The dose-response characteristics of transcranial direct current stimulation (tDCS) remain uncertain but may be related to variability in brain electric fields due to individual anatomical factors. Here, we investigated whether the electric fields influence the responses to motor cortical tDCS. In a randomized cross-over design, 21 participants underwent 10 min of anodal tDCS with 0.5, 1.0, 1.5, or 2.0 mA or sham. Compared to sham, all active conditions increased the size of motor evoked potentials (MEP) normalized to the pre-tDCS baseline, irrespective of anterior or posterior magnetic test stimuli. The electric field calculated in the motor cortex of each participant had a nonlinear effect on the normalized MEP size, but its effects were small compared to those of other participant-specific factors. The findings support the efficacy of anodal tDCS in enhancing the MEP size but do not demonstrate any benefits of personalized electric field modeling in explaining tDCS response variability.