Modulation of mind wandering using transcranial direct current stimulation: A meta-analysis based on electric field modeling.

Mind wandering (MW) is a heterogeneous construct involving task-unrelated thoughts. Recently, the interest in modulating MW propensity via non-invasive brain stimulation techniques has increased. Single-session transcranial direct current stimulation (tDCS) in healthy controls has led to mixed results in modulating MW propensity, possibly due to methodological heterogeneity. Therefore, our aim was to conduct a systematic meta-analysis to examine the influence of left dorsolateral prefrontal cortex (lDLPFC) and right inferior parietal lobule (rIPL) targeted tDCS on MW propensity. Importantly, by computational modeling of tDCS-induced electric fields, we accounted for differences in tDCS-dose across studies that varied strongly in their applied methodology. Fifteen single-session, sham-controlled tDCS studies published until October 2021 were included. All studies involved healthy adult participants and used cognitive tasks combined with MW thought-probes. Heterogeneity in tDCS electrode placement, stimulation polarity and intensity were controlled for by means of electric field simulations, while overall methodological quality was assessed via an extended risk of bias (RoB) assessment. We found that RoB was the strongest predictor of study outcomes. Moreover, the rIPL was the most promising cortical area for influencing MW, with stronger anodal electric fields in this region being negatively associated with MW propensity. Electric field strength in the lDLPFC was not related to MW propensity. We identified several severe methodological problems that could have contributed to overestimated effect sizes in this literature, an issue that needs urgent attention in future research in this area. Overall, there is no reliable evidence for tDCS influencing MW in the healthy. However, the analysis also revealed that increasing neural excitability in the rIPL via tDCS might be associated with reduced MW propensity. In an exploratory approach, we also found some indication that targeting prefrontal regions outside the lDLPFC with tDCS could lead to increased MW propensity.

Enhancement of dielectrophoresis-based particle collection from high conducting fluids due to partial electrode insulation.

Dielectrophoresis (DEP) is a successful method to recover nanoparticles from different types of fluid. The DEP force acting on these particles is created by an electrode microarray that produces a nonuniform electric field. To apply DEP to a highly conducting biological fluid, a protective hydrogel coating over the metal electrodes is required to create a barrier between the electrode and the fluid. This protects the electrodes, reduces the electrolysis of water, and allows the electric field to penetrate into the fluid sample. We observed that the protective hydrogel layer can separate from the electrode and form a closed domed structure and that collection of 100 nm polystyrene beads increased when this occurred. To better understand this collection increase, we used COMSOL Multiphysics software to model the electric field in the presence of the dome filled with different materials ranging from low-conducting gas to high conducting phosphate-buffered saline fluids. The results suggest that as the electrical conductivity of the material inside the dome is reduced, the whole dome acts as an insulator which increases electric field intensity at the electrode edge. This increased intensity widens the high-intensity electric field factor zone resulting in increased collection. This informs how dome formation results in increased particle collection and provides insight into how the electric field can be intensified to the increase collection of particles. These results have important applications for increasing the recovery of biologically-derived nanoparticles from undiluted physiological fluids that have high conductance, including the collection of cancer-derived extracellular vesicles from plasma for liquid biopsy applications.

Computation of transcranial magnetic stimulation electric fields using self-supervised deep learning.

Electric fields (E-fields) induced by transcranial magnetic stimulation (TMS) can be modeled using partial differential equations (PDEs). Using state-of-the-art finite-element methods (FEM), it often takes tens of seconds to solve the PDEs for computing a high-resolution E-field, hampering the wide application of the E-field modeling in practice and research. To improve the E-field modeling's computational efficiency, we developed a self-supervised deep learning (DL) method to compute precise TMS E-fields. Given a head model and the primary E-field generated by TMS coils, a DL model was built to generate a E-field by minimizing a loss function that measures how well the generated E-field fits the governing PDE. The DL model was trained in a self-supervised manner, which does not require any external supervision. We evaluated the DL model using both a simulated sphere head model and realistic head models of 125 individuals and compared the accuracy and computational speed of the DL model with a state-of-the-art FEM. In realistic head models, the DL model obtained accurate E-fields that were significantly correlated with the FEM solutions. The DL model could obtain precise E-fields within seconds for whole head models at a high spatial resolution, faster than the FEM. The DL model built for the simulated sphere head model also obtained an accurate E-field whose average difference from the analytical E-fields was 0.0054, comparable to the FEM solution. These results demonstrated that the self-supervised DL method could obtain precise E-fields comparable to the FEM solutions with improved computational speed.

Electric Field Strength From Prefrontal Transcranial Direct Current Stimulation Determines Degree of Working Memory Response: A Potential Application of Reverse-Calculation Modeling?

BACKGROUND: Transcranial direct current stimulation (tDCS) for working memory is an enticing treatment, but there is mixed evidence to date. OBJECTIVES: We tested the effects of electric field strength from uniform 2 mA dosing on working memory change from prestimulation to poststimulation. Second, we statistically evaluated a reverse-calculation method of individualizing tDCS dose and its effect on normalizing electric field at the cortex. MATERIALS AND METHODS: We performed electric field modeling on a data set of 28 healthy older adults (15 women, mean age = 73.7, SD = 7.3) who received ten sessions of active 2 mA tDCS (N = 14) or sham tDCS (N = 14) applied over bilateral dorsolateral prefrontal cortices (DLPFC) in a triple-blind design. We evaluated the relationship between electric field strength and working memory change on an N-back task in conditions of above-median, high electric field from active 2 mA (N = 7), below-median, low electric field from active 2 mA (N = 7), and sham (N = 14) at regions of interest (ROI) at the left and right DLPFC. We then determined the individualized reverse-calculation dose to produce the group average electric field and measured the electric field variance between uniform 2 mA doses vs individualized reverse-calculation doses at the same ROIs. RESULTS: Working memory improvements from pre- to post-tDCS were significant for the above-median electric field from active 2 mA condition at the left DLPFC (mixed ANOVA, p = 0.013). Furthermore, reverse-calculation modeling significantly reduced electric field variance at both ROIs (Levene's test; p < 0.001). CONCLUSIONS: Higher electric fields at the left DLPFC from uniform 2 mA doses appear to drive working memory improvements from tDCS. Individualized doses from reverse-calculation modeling significantly reduce electric field variance at the cortex. Taken together, using reverse-calculation modeling to produce the same, high electric fields at the cortex across participants may produce more effective future tDCS treatments for working memory.

Safety and chronic lesion characterization of pulsed field ablation in a Porcine model.

BACKGROUND: Pulsed field ablation (PFA) has been identified as an alternative to thermal-based ablation systems for treatment of atrial fibrillation patients. The objective of this Good Laboratory Practice (GLP) study was to characterize the chronic effects and safety of overlapping lesions created by a PFA system at intracardiac locations in a porcine model. METHODS: A circular catheter with nine gold electrodes was used for overlapping low- or high-dose PFA deliveries in the superior vena cava (SVC), right atrial appendage (RAA), and right superior pulmonary vein (RSPV) in six pigs. Electrical isolation was evaluated acutely and chronic lesions were assessed via necropsy and histopathology after 4-week survival. Acute and chronic safety data were recorded peri- and post-procedurally. RESULTS: No animal experienced ventricular arrhythmia during PFA delivery, and there was no evidence of periprocedural PFA-related adverse events. Lesions created in all anatomies resulted in electrical isolation postprocedure. Lesions were circumferential, contiguous, and transmural, with all converting into consistent lines of chronic replacement fibrosis, regardless of trabeculated or smooth endocardial surface structure. Ablations were non-thermally generated with only minimal post-delivery temperature rises recorded at the electrodes. There was no evidence of extracardiac damage, stenosis, aneurysms, endocardial disruption, or thrombus. CONCLUSION: PFA deliveries to the SVC, RAA, and RSPV resulted in complete circumferential replacement fibrosis at 4-week postablation with an excellent chronic myocardial and collateral tissue safety profile. This GLP study evaluated the safety and efficacy of a dosage range in preparation for a clinical trial and characterized the non-thermal nature of PFA.

Association between tDCS computational modeling and clinical outcomes in depression: data from the ELECT-TDCS trial.

Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation intervention investigated for the treatment of depression. Clinical results have been heterogeneous, partly due to the variability of electric field (EF) strength in the brain owing to interindividual differences in head anatomy. Therefore, we investigated whether EF strength was correlated with behavioral changes in 16 depressed patients using simulated electric fields in real patient data from a controlled clinical trial. We hypothesized that EF strength in the dorsolateral prefrontal cortex (DLPFC) and anterior cingulate cortex (ACC), brain regions implicated in depression pathophysiology, would be associated with changes in depression, mood and anxiety scores. SimNIBS were used to simulate individual electric fields based on the MRI structural T1-weighted brain scans of depressed subjects. Linear regression models showed, at the end of the acute treatment phase, that simulated EF strength was inversely associated with negative affect in the bilateral ACC (left: ß = - 160.463, CI [- 291.541, - 29.385], p = 0.021; right: ß = - 189.194, CI [- 289.479, - 88.910], p = 0.001) and DLPFC (left: ß = - 93.210, CI [- 154.960, - 31.461], p = 0.006; right: ß = - 82.564, CI [- 142.867, - 22.262], p = 0.011) and with depression scores in the left ACC (ß = - 156.91, CI [- 298.51, - 15.30], p = 0.033). No association between positive affect or anxiety scores, and simulated EF strength in the investigated brain regions was found. To conclude, our findings show preliminary evidence that EF strength simulations might be associated with further behavioral changes in depressed patients, unveiling a potential mechanism of action for tDCS. Further studies should investigate whether individualization of EF strength in key brain regions impact clinical response.

An experimental system for real-time fluorescence recordings of cell membrane changes induced by electroporation.

The electroporation of cells is nowadays used for a large variety of purposes, from basic research to cancer therapy and food processing. Understanding molecular mechanisms of the main processes involved in electroporation is thus of significant interest. In the present work, we propose an experimental system to record in real time the evolution of any cell parameter which can be evaluated by fluorescence (before, during and after application of the electroporation pulses to cells in suspension). The system is based on the design of adequate electroporation electrodes, compatible with a standard spectrofluorometer cuvette housing. The electric field intensity generated when pulses are applied was carefully characterized for different geometries of the electrodes, to choose a construction ensuring the greatest homogeneity of the field in combination with the best possible illumination of the sample. As an example of the method's application, we present here generalized polarization kinetics for a varying number of electroporation pulses applied to a cell suspension; the general polarization parameter is strongly correlated to water presence in the hydrophobic membrane core. The system may be used for many other fluorescence measurements useful for the characterization of the electroporation process.

Neuromodulatory transcranial magnetic stimulation (TMS) changes functional connectivity proportional to the electric-field induced by the TMS pulse.

OBJECTIVE: Transcranial magnetic stimulation (TMS) can efficiently and robustly modulate synaptic plasticity, but little is known about how TMS affects functional connectivity (rs-fMRI). Accordingly, this project characterized TMS-induced rsFC changes in depressed patients who received 3 days of left prefrontal intermittent theta burst stimulation (iTBS). METHODS: rs-fMRI was collected from 16 subjects before and after iTBS. Correlation matrices were constructed from the cleaned rs-fMRI data. Electric-field models were conducted and used to predict pre-post changes in rs-fMRI. Site by orientation heatmaps were created for vectors centered on the stimulation site and a control site (contralateral motor cortex). RESULTS: For the stimulation site, there was a clear relationship between both site and coil orientation, and connectivity changes. As distance from the stimulation site increased, prediction accuracy decreased. Similarly, as eccentricity from the optimal orientation increased, prediction accuracy decreased. The systematic effects described above were not apparent in the heatmap centered on the control site. CONCLUSIONS: These results suggest that rs-fMRI following iTBS changes systematically as a function of the distribution of electrical energy delivered from the TMS pulse, as represented by the e-field model. SIGNIFICANCE: This finding lays the groundwork for future studies to individualize TMS targeting based on how predicted rs-fMRI changes might impact psychiatric symptoms.

EFMouse: a Matlab toolbox to model electric fields in the mouse brain.

Compared to the rapidly growing literature on transcranial electrical stimulation (tES) in humans, research into the mechanisms underlying neuromodulation by tES using in-vivo animal models is growing but still relatively rare. Such research, however, is key to overcoming experimental limitations in humans and essential to build a detailed understanding of the in-vivo consequences of tES that can ultimately lead to development of targeted and effective therapeutic applications of noninvasive brain stimulation. The sheer difference in scale and geometry between animal models and the human brain contributes to the complexity of designing and interpreting animal studies. Here we extend previous approaches to model intracranial electric fields to generate predictions that can be tested with in-vivo intracranial recordings. Although the toolbox has general applicability and could be used to predict intracranial fields for any tES study using mice, we illustrate its usage by comparing fields in a high-density multi-electrode montage with a more traditional two electrode montage. Our simulations show that both montages can produce strong focal homogeneous electric fields in targeted areas. However, the high-density montage produces a field that is more perpendicular to the visual cortical surface, which is expected to result in larger changes in neuronal excitability.

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.

HD-tDCS induced changes in resting-state functional connectivity: Insights from EF modeling.

BACKGROUND: High-definition transcranial direct current stimulation (HD-tDCS) holds promise for therapeutic use in psychiatric disorders. One obstacle for the implementation into clinical practice is response variability. One way to tackle this obstacle is the use of Individualized head models. OBJECTIVE: This study investigated the variability of HD-tDCS induced electric fields (EFs) and its impact on resting-state functional connectivity (rsFC) during different time windows. METHODS: In this randomized, double-blind, and sham controlled study, seventy healthy males underwent 20 min of 1.5 mA HD-tDCS on the right inferior frontal gyrus (rIFG) while undergoing resting-state functional magnetic resonance imaging (rs-fMRI). Individual head models and EF simulations were created from anatomical images. The effects of HD-tDCS on rsFC were assessed using a seed-to-voxel analysis. A subgroup analysis explored the relationship between EF magnitude and rsFC during different stimulation time windows. RESULTS: Results highlighted significant variability in HD-tDCS-induced EFs. Compared to the sham group, the active group showed increased rsFC between the rIFG and the left prefrontal cortex, during and after stimulation. During active stimulation, EF magnitude correlated positively with rsFC between the rIFG and the left hippocampus initially, and negatively during the subsequent period. CONCLUSION: This study indicated an HD-tDCS induced increase of rsFC between left and right prefrontal areas. Furthermore, an interaction between the magnitude and the duration of HD-tDCS on rsFC was observed. Due to the high EF variability that was apparent, these findings highlight the need for individualized HD-tDCS protocols and the creation of head models to optimize effects and reduce response heterogeneity.

Individual electric field predicts functional connectivity changes after anodal transcranial direct-current stimulation in chronic stroke.

The neuromodulation effect of anodal tDCS is not thoroughly studied, and the heterogeneous profile of stroke individuals with brain lesions would further complicate the stimulation outcomes. This study aimed to investigate the functional changes in sensorimotor areas induced by anodal tDCS and whether individual electric field could predict the functional outcomes. Twenty-five chronic stroke survivors were recruited and divided into tDCS group (n = 12) and sham group (n = 13). Increased functional connectivity (FC) within the surrounding areas of ipsilesional primary motor cortex (M1) was only observed after anodal tDCS. Averaged FC among the ipsilesional sensorimotor regions was observed to be increased after anodal tDCS (t(11) = 2.57, p = 0.026), but not after sham tDCS (t(12) = 0.69, p = 0.50). Partial least square analysis identified positive correlations between electric field (EF) strength normal to the ipsilesional M1 surface and individual FC changes in tDCS group (r = 0.84, p < 0.001) but not in sham group (r = 0.21, p = 0.5). Our results indicated anodal tDCS facilitates the FC within the ipsilesional sensorimotor network in chronic stroke subjects, and individual electric field predicts the functional outcomes.

Modelling the differential effects of age on transcranial magnetic stimulation induced electric fields.

Objective. The therapeutic application of noninvasive brain stimulation modalities such as transcranial magnetic stimulation (TMS) has expanded in terms of indications and patient populations. Often neurodevelopmental and neurodegenerative changes are not considered in research studies and clinical applications. This study sought to examine TMS dosing across time points in the life cycle.Approach. TMS induced electric fields with a figure-of-eight coil was simulated at left dorsolateral prefrontal cortex regions and taken in vertex as a control region. Realistic magnetic resonance imaging-based head models (N= 48) were concurrently examined in a cross-sectional study of three different age groups (children, adults, and elderlies).Main results. Age had a negative correlation with electric field peaks in white matter, grey matter and cerebrospinal fluid (P< 0.001). Notably, the electric field map in children displayed the widest cortical surface spread of TMS induced electric fields.Significance. Age-related anatomical geometry beneath the coil stimulation site had a significant impact on the TMS induced electric fields for different age groups. Safety considerations for TMS applications and protocols in children are warranted based on the present electric field findings.

Transcranial magnetic stimulation mapping of the motor cortex: comparison of five estimation algorithms.

Background: There are currently five different kinds of transcranial magnetic stimulation (TMS) motor mapping algorithms available, from ordinary point-based algorithms to advanced field-based algorithms. However, there have been only a limited number of comparison studies conducted, and they have not yet examined all of the currently available algorithms. This deficiency impedes the judicious selection of algorithms for application in both clinical and basic neuroscience, and hinders the potential promotion of a potential superior algorithm. Considering the influence of algorithm complexity, further investigation is needed to examine the differences between fMRI peaks and TMS cortical hotspots that were identified previously. Methods: Twelve healthy participants underwent TMS motor mapping and a finger-tapping task during fMRI. The motor cortex TMS mapping results were estimated by five algorithms, and fMRI activation results were obtained. For each algorithm, the prediction error was defined as the distance between the measured scalp hotspot and optimized coil position, which was determined by the maximum electric field strength in the estimated motor cortex. Additionally, the study identified the minimum number of stimuli required for stable mapping. Finally, the location difference between the TMS mapping cortical hotspot and the fMRI activation peak was analyzed. Results: The projection yielded the lowest prediction error (5.27 ± 4.24 mm) among the point-based algorithms and the association algorithm yielded the lowest (6.66 ± 3.48 mm) among field-based estimation algorithms. The projection algorithm required fewer stimuli, possibly resulting from its suitability for the grid-based mapping data collection method. The TMS cortical hotspots from all algorithms consistently deviated from the fMRI activation peak (20.52 ± 8.46 mm for five algorithms). Conclusion: The association algorithm might be a superior choice for clinical applications and basic neuroscience research, due to its lower prediction error and higher estimation sensitivity in the deep cortical structure, especially for the sulcus. It also has potential applicability in various other TMS domains, including language area mapping and more. Otherwise, our results provide further evidence that TMS motor mapping intrinsically differs from fMRI motor mapping.

Continuous Theta-Burst Stimulation to the Right Dorsolateral Prefrontal Cortex May Increase Potentiated Startle in Healthy Individuals.

Background: Convergent neuroimaging and neuromodulation studies implicate the right dorsolateral prefrontal cortex (dlPFC) as a key region involved in anxiety-cognition interactions. However, neuroimaging data are correlational, and neuromodulation studies often lack appropriate methodological controls. Accordingly, this work was designed to explore the role of right prefrontal cognitive control mechanisms in the expression/regulation of anxiety using continuous theta-burst transcranial magnetic stimulation (cTBS) and threat of unpredictable shock. Based on prior neuromodulation studies, we hypothesized that the right dlPFC contributed to anxiety expression, and that cTBS should downregulate this expression. Methods: We measured potentiated startle and performance on the Sternberg working memory paradigm in 28 healthy participants before and after 4 sessions (600 pulses/session) of active or sham cTBS. Stimulation was individualized to the right dlPFC site of maximal working memory-related activity and optimized using electric-field modeling. Results: Compared with sham cTBS, active cTBS, which is thought to induce long-term depression-like synaptic changes, increased startle during threat of shock, but the effect was similar for predictable and unpredictable threat. As a measure of target (dis)engagement, we also showed that active but not sham cTBS decreased accuracy on the Sternberg task. Conclusions: Counter to our initial hypothesis, cTBS to the right dlPFC made individuals more anxious, rather than less anxious. Although preliminary, these results are unlikely to be due to transient effects of the stimulation, because anxiety was measured 24 hours after cTBS. In addition, these results are unlikely to be due to off-target effects, because target disengagement was evident from the Sternberg performance data.

The Predictive Value of Individual Electric Field Modeling for Transcranial Alternating Current Stimulation Induced Brain Modulation.

There is considerable individual variability in the reported effectiveness of non-invasive brain stimulation. This variability has often been ascribed to differences in the neuroanatomy and resulting differences in the induced electric field inside the brain. In this study, we addressed the question whether individual differences in the induced electric field can predict the neurophysiological and behavioral consequences of gamma band tACS. In a within-subject experiment, bi-hemispheric gamma band tACS and sham stimulation was applied in alternating blocks to the participants' superior temporal lobe, while task-evoked auditory brain activity was measured with concurrent functional magnetic resonance imaging (fMRI) and a dichotic listening task. Gamma tACS was applied with different interhemispheric phase lags. In a recent study, we could show that anti-phase tACS (180° interhemispheric phase lag), but not in-phase tACS (0° interhemispheric phase lag), selectively modulates interhemispheric brain connectivity. Using a T1 structural image of each participant's brain, an individual simulation of the induced electric field was computed. From these simulations, we derived two predictor variables: maximal strength (average of the 10,000 voxels with largest electric field values) and precision of the electric field (spatial correlation between the electric field and the task evoked brain activity during sham stimulation). We found considerable variability in the individual strength and precision of the electric fields. Importantly, the strength of the electric field over the right hemisphere predicted individual differences of tACS induced brain connectivity changes. Moreover, we found in both hemispheres a statistical trend for the effect of electric field strength on tACS induced BOLD signal changes. In contrast, the precision of the electric field did not predict any neurophysiological measure. Further, neither strength, nor precision predicted interhemispheric integration. In conclusion, we found evidence for the dose-response relationship between individual differences in electric fields and tACS induced activity and connectivity changes in concurrent fMRI. However, the fact that this relationship was stronger in the right hemisphere suggests that the relationship between the electric field parameters, neurophysiology, and behavior may be more complex for bi-hemispheric tACS.

Automated optimization of TMS coil placement for personalized functional network engagement.

Transcranial magnetic stimulation (TMS) is used to treat multiple psychiatric and neurological conditions by manipulating activity in particular brain networks and circuits, but individual responses are highly variable. In clinical settings, TMS coil placement is typically based on either group average functional maps or scalp heuristics. Here, we found that this approach can inadvertently target different functional networks in depressed patients due to variability in their functional brain organization. More precise TMS targeting should be feasible by accounting for each patient's unique functional neuroanatomy. To this end, we developed a targeting approach, termed targeted functional network stimulation (TANS). The TANS approach improved stimulation specificity in silico in 8 highly sampled patients with depression and 6 healthy individuals and in vivo when targeting somatomotor functional networks representing the upper and lower limbs. Code for implementing TANS and an example dataset are provided as a resource.

Numerical Study on Electrode Design for Rodent Deep Brain Stimulation With Implantations Cranial to Targeted Nuclei.

The globus pallidus internus and the subthalamic nucleus are common targets for deep brain stimulation to alleviate symptoms of Parkinson's disease and dystonia. In the rodent models, however, their direct targeting is hindered by the relatively large dimensions of applied electrodes. To reduce the neurological damage, the electrodes are usually implanted cranial to the nuclei, thus exposing the non-targeted brain regions to large electric fields and, in turn, possible undesired stimulation effects. In this numerical study, we analyze the spread of the fields for the conventional electrodes and several modifications. As a result, we present a relatively simple electrode design that allows an efficient focalization of the stimulating field in the inferiorly located nuclei.

Comparison of electric field modeling pipelines for transcranial direct current stimulation.

OBJECTIVES: Electric field modeling utilizes structural brain magnetic resonance images (MRI) to model the electric field induced by non-invasive transcranial direct current stimulation (tDCS) in a given individual. Electric field modeling is being integrated with clinical outcomes to improve understanding of inter-individual variability in tDCS effects and to optimize tDCS parameters, thereby enhancing the predictability of clinical effects. The successful integration of modeling in clinical use will primarily be driven by choice of tools and procedures implemented in computational modeling. Thus, the electric field predictions from different modeling pipelines need to be investigated to ensure the validity and reproducibility of tDCS modeling results across clinical or translational studies. METHODS: We used T1w structural MRI from 32 healthy volunteer subjects and modeled the electric field distribution for a fronto-temporal tDCS montage. For five different computational modeling pipelines, we quantitatively compared brain tissue segmentation and electric field predicted in whole-brain, brain tissues and target brain regions between the modeling pipelines. RESULTS: Our comparisons at various levels did not reveal any systematic trend with regards to similarity or dissimilarity of electric field predicted in brain tissues and target brain regions. The inconsistent trends in the predicted electric field indicate variation in the procedures, routines and algorithms used within and across the modeling pipelines. CONCLUSION: Our results suggest that studies integrating electric field modeling and clinical outcomes of tDCS will highly depend upon the choice of the modeling pipelines and procedures. We propose that using these pipelines for further research and clinical applications should be subject to careful consideration, and indicate general recommendations.

Identifying regions in prefrontal cortex related to working memory improvement: A novel meta-analytic method using electric field modeling.

Altering cortical activity using transcranial direct current stimulation (tDCS) has been shown to improve working memory (WM) performance. Due to large inter-experimental variability in the tDCS montage configuration and strength of induced electric fields, results have been mixed. Here, we present a novel meta-analytic method relating behavioral effect sizes to electric field strength to identify brain regions underlying largest tDCS-induced WM improvement. Simulations on 69 studies targeting left prefrontal cortex showed that tDCS electric field strength in lower dorsolateral prefrontal cortex (Brodmann area 45/47) relates most strongly to improved WM performance. This region explained 7.8 % of variance, equaling a medium effect. A similar region was identified when correlating WM performance and electric field strength of right prefrontal tDCS studies (n = 18). Maximum electric field strength of five previously used tDCS configurations were outside of this location. We thus propose a new tDCS montage which maximizes the tDCS electric field strength in that brain region. Our findings can benefit future tDCS studies that aim to affect WM function.