Biology subjects

Thielscher, A.

Publications and source records attributed to Thielscher, A..

At least 19 recordsLinked to original sources

bioRxiv2026

Multicenter reliability of electric field simulations: Evidence from a traveling-subjects study

Multicenter neuroimaging studies face challenges from scanner-related measurement biases that can obscure biological effects. Traveling-subject (TS) designs allow direct quantification of such biases by scanning the same participants across multiple sites. While reliability of structural, functional, and diffusion MRI has been established, the reliability of electric field simulations for transcranial brain stimulation has not been examined. We assessed inter-scanner and scan-rescan reliability of simulated electric field magnitudes in 10 participants scanned twice on each of five 3T Siemens scanners, using SimNIBS v4.1 to simulate focal tDCS across seven cortical and cerebellar targets. ICC values indicated good to excellent inter-scanner (0.86-0.97) and scan-rescan (0.94-0.98) reliability, with between-scanner variance not exceeding measurement error. Intra-individual segmentation variability substantially explained within-person differences in field magnitudes, whereas image quality did not predict segmentation variability. These results demonstrate that individualized electric field simulations are robust to scanner-related variation, supporting their use in multicenter brain stimulation research.

neuroscience↗

bioRxiv2026

Histologically Informed Multiscale Modeling of the Neuronal Elements Activated by TMS

BackgroundThe primary neural site(s) at which action potentials are initiated by transcranial magnetic stimulation (TMS) remain poorly understood. Multiscale computational models provide biophysically based hypotheses, but model accuracy is constrained by limited histological knowledge of the microscopic organization of neural tissue. Recent high-resolution electron microscopy, in particular the petavoxel H01 dataset, provides novel, detailed axon morphologies and myelination patterns within the human cortex and superficial white matter. ObjectiveTo compare systematically multiple candidates for the neural elements activated by TMS using computer simulations informed by an extensive body of histological measurements, including neuron models directly reconstructed from the H01 dataset. MethodsWe developed a novel modeling pipeline to extract individual morphologically realistic multi-compartment models with exact myelination from serial section electron microscopic segmentations. To assess candidate excitation sites, we simulated the extracted neuron models together with parameterized models of a "ball-and-two-sticks", bifurcation, termination, and bend under uniform electric fields. In addition, smooth and sharply bending myelinated axons were embedded in a realistic human head model to evaluate activation thresholds under anatomically realistic electric field distributions. ResultsAxon terminations were only excitable by TMS when they were fully myelinated, which the histology suggested is unlikely. Partial myelination, even when separated by only 10 {micro}m from the terminal, increased activation thresholds by more than 100%. Reconstructed H01 neurons exhibited correspondingly high activation thresholds at axon terminals due to a lack of myelination. Further, most other candidate structures exhibited low thresholds only for histologically unrealistic parameter choices. In contrast, myelinated axonal bends of fibers transitioning from cortex to superficial white matter consistently showed low activation thresholds for both uniform electric fields and in realistic head model simulations. These thresholds fell within physiologically realistic ranges and, for larger diameter fibers, approached experimentally measured motor thresholds. ConclusionThese results identify myelinated axons bending from cortex into superficial white matter as possible neural targets for transcranial magnetic stimulation, and demonstrate the relevance of detailed histological and biophysical information to support robust modeling results.

neuroscience↗

bioRxiv2026

Harmonizing the stimulation dose of focal tDCS across target sites

Non-invasive brain stimulation is an established tool for modulating neural activity that holds promise for advancing both cognitive neuroscience and clinical interventions. Focal transcranial direct current stimulation (tDCS), using center-surround electrode montages, enables more region-specific targeting. Although computational models can simulate individual electric fields, no existing approach enables the prospective individualization of electrode placement while standardizing the dose across targeted brain regions. In the current preparatory methodological study, we present a modeling-based framework that harmonizes the electric field strength between different target regions at the group level, but preserves inter-individual variability. This enables systematic examination of dose-response relationships and their regional differences. Positioning of the center-surround electrode montages is individualized to ensure focusing of the electric field on the target regions. We started by defining brain targets for eight cognitive and motor functions using MRI data from 43 participants. Using field simulations, we then estimated a group-average field strength in the target regions that had led to behavioral and physiological effects in prior tDCS studies (resulting in 0.2 V/m). The radii of the center-surround montages were optimized for each target region to achieve the intended field strength while maximizing focality. Validation in an independent sample (n=53) confirmed that the intended target field strength is achieved on average for new participants. The described computational tools are made available as open-source software, allowing other researchers to apply our individualization framework with parameters (target regions and target field strengths) tailored to their specific research questions; and are currently being implemented in a multi-center study involving approximately 1,000 datasets.

neuroscience↗

bioRxiv2026

No group-level changes in corticospinal excitability following low-intensity theta-burst ultrasound stimulation of the primary motor hand area.

BackgroundLow-intensity transcranial ultrasound stimulation (TUS) is a novel non-invasive brain-stimulation technique offering high spatial precision and depth penetrance. Theta burst TUS (tbTUS), featuring a temporal theta burst stimulation pattern, has been reported to facilitate corticomotor excitability, when applied to the human primary motor hand area (M1-HAND). However, replication attempts have yielded inconsistent results. MethodsFifteen healthy human participants underwent neuronavigated tbTUS targeting the left M1-HAND in the anterior wall of the precentral sulcus, as well as anterior and posterior active control sites. The three tbTUS conditions were applied in counterbalanced order on separate days. Corticospinal excitability was assessed via motor evoked potentials (MEPs) recorded before and 5, 15, 30, and 60 minutes after tbTUS, and analyzed using an rmANOVA. ResultsNone of the tbTUS conditions produced consistent group-level changes in MEP amplitude at any time point. Both intra- and inter-subject variability were high, and individual MEP changes following precentral tbTUS did not correlate with changes after control-site stimulation. ConclusionsWe did not observe reliable modulatory effects of neuronavigated tbTUS on corticospinal excitability. Methodological and hardware differences may account for discrepancies across studies. Our findings align with recent reports questioning the robustness of tbTUS-induced facilitation.

neuroscience↗

bioRxiv2025

Deep learning to overcome human error and bias in electrode position extraction in tDCS-fMRI studies

Combining transcranial direct current stimulation (tDCS) with fMRI enables investigation of stimulation effects, while structural MRI verifies electrode positioning, critical for focal montages where minor misplacements reduce target current dose. Currently, no fully automated methods exist for precise electrode extraction from MRI. We developed an Attention U-Net-based deep learning approach to automate electrode detection in focal tDCS-fMRI studies, using structural pointwise-encoding time reduction with radial acquisition (PETRA) MRI scans from a multicenter trial (N = 392 images; 1,568 electrodes, https://www.memoslap.de/en/home/). Performance was compared to manual and semi-automated methods for a 3x1 montage (three cathodes around a central anode). The network achieved robust segmentation (Dice Score = 0.76, Hausdorff distance = 36.76 mm), identifying all electrodes in 95% of cases (323/340). These metrics compared network-segmented electrodes to highly accurate, manually segmented electrodes, which are also called "ground truth". Linear mixed-effects models on 52 "ground truth" images showed deep learning outperformed manual and semi-automated methods, aligning best with ground truth. Fully/semi-automated methods comparison of 290 images showed highest agreement (ICC = 0.990, bias = 1.3 mm), while manual extraction exhibited larger biases (-5.77 to -7.06 mm) and systematic errors. The automated approach overcomes manual limitations by improving precision, eliminating human variability and bias, and enabling scalability for large studies. It sets a new standard for electrode verification in focal tDCS, particularly for studies requiring precise localization. The model is open-source, with future refinements discussed

neuroscience↗

bioRxiv2025

A New Method for Optimal Placement of Tumor Treating Fields Electrodes

OverviewTumor Treating Fields (TTFields) provide a non-invasive treatment option for newly diagnosed glioblastoma. While optimization of electrode placement is important to increase treatment efficacy, clinical therapy planning is done using an undisclosed and proprietary software (NovoTAL(R)), which is clinically unvalidated. This study investigates a new computational approach for optimizing TTFields electrode placement and is compared to the current clinical standard. MethodsWe developed a new computational pipeline integrating patient-specific anatomical data to optimize electrode configurations in five representative glioblastoma cases with diverse tumor locations and sizes. Two optimization strategies were employed: one maximizing electric field intensity at the tumor, and another enhancing coverage of the adjacent brain while maintaining sufficient tumor intensity. Results were compared to electrode placements generated by NovoTAL(R). Additional simulations with artificial tumors assessed the effects of tumor size and location. ResultsOptimized electrode placements improved electric field intensity in tumors by 18%-34% compared to the clinical standard. Coverage-weighted optimizations provided broader field coverage without significantly compromising tumor intensity. Smaller or surface-adjacent tumors benefited most from optimization, achieving precise targeting and enhanced coverage. Extensive randomized placement analyses highlighted the superior performance of the optimized configurations. Analysis of artificial models showed consistent improvements across varying tumor locations and sizes. ConclusionPersonalized optimization of TTFields electrode placement significantly improves electric field targeting of tumors and adjacent brain regions. This approach outperforms standardized planning software and clinical practices and supports future development of adaptive, automated strategies for individualized TTFields therapy in glioblastoma. Keypoints- Optimized TTFields array placement enhanced field intensity by 18-34% vs. clinical standard. - Optimized TTFields planning improved field coverage in tumor-adjacent regions. - Optimized TTFields planning outperformed standard methods and random placement. Importance of the studyTTFields are increasingly used as adjuvant therapy for glioblastoma. However, current individualized treatment planning relies on proprietary, undisclosed, and clinically unvalidated software, limiting transparency, optimization, and innovation in the field. This study introduces an individualized, semi-automated, and open-source method for optimal electrode placement based on standard MRI data, addressing a critical need for validated and adaptable planning tools. Our approach increased field intensity in tumors by 18-34% and achieved broader coverage compared to the standard clinical tool (NovoTAL(R)), without compromising therapeutic strength. Notably, the method also consistently outperformed extensive random electrode placements across diverse tumor types and sizes, highlighting its robustness and ability to achieve true optimal configurations. Open-source availability enhances reproducibility and clinical translation, representing a significant step toward more effective, individualized TTFields therapy. This advancement has the potential to improve outcomes for glioblastoma patients and underscores the importance of technology validation in neuro-oncology.

neuroscience↗

bioRxiv2025

TI-Toolbox: An Open-Source Software for Temporal Interference Stimulation Research

BackgroundTemporal interference stimulation is a novel non-invasive brain stimulation approach that promises selective targeting of deep brain structures while minimizing off-target cortical stimulation. Despite a growing interest in temporal interference applications, there is a need for integrated computational tools that seamlessly connect neuroimaging data preprocessing through montage optimization, field simulation, and analysis within a unified framework designed for translational and clinical research. MethodsWe developed TI-Toolbox, an open-source software platform that integrates established neuroimaging tools (dcm2niix, SimNIBS, FreeSurfer) with specialized algorithms for temporal interference research. The platform provides end-to-end workflows encompassing structural MRI preprocessing, volume conduction modeling, montage optimization, electric field simulation, and region-of-interest analysis. Both graphical user interface and command-line interface implementations ensure accessibility across user expertise levels. The platform employs containerized deployment via Docker to ensure reproducibility and cross-platform compatibility. ResultsTI-Toolbox successfully automates the complete temporal interference research pipeline, from DICOM conversion through final field analysis. The platform demonstrates robust performance across operating systems and provides standardized workflows that enhance reproducibility. Furthermore, our case studies support the validity of our HD-EEG mapping approach for montage standardization and the need for individualized modeling for exposure assessment. ConclusionsTI-Toolbox addresses critical infrastructure gaps in temporal interference research by providing researchers with a unified, validated platform that reduces technical barriers and accelerates translational research in non-invasive deep brain stimulation. HighlightsO_LIOpen-source platform unifying TI stimulation workflow end-to-end C_LIO_LIDocker deployment ensures reproducibility across operating systems C_LIO_LIHD-EEG electrode mapping preserves field characteristics C_LIO_LIStandardized model is sufficient for montage optimization C_LIO_LIAnatomical differences explain >40% of inter-individual variability C_LI

neuroscience↗

bioRxiv2025

Optimizing and assessing multichannel TMS focality

BackgroundMultichannel transcranial magnetic stimulation (mTMS) enables electronic steering of induced electric fields across multiple cortical targets without physical coil repositioning, addressing key limitations of conventional single-channel TMS (sTMS). However, determining optimal input currents for focal stimulation remains challenging, and different mTMS systems have not been systematically compared under realistic hardware constraints. ObjectiveTo develop an user-centric framework for optimizing and assessing mTMS focality by introducing a generic optimization algorithm, establishing meaningful quality metrics, and comparing mTMS coil arrays with traditional single-channel TMS across cortical targets. MethodsWe developed a fast optimization framework incorporating target E-field constraints via parametrization of degenerated hyperellipsoids, explicitly integrating current-rate limits, for example from stimulator electronics and coil heating. Using high-resolution finite-element models of nine individual brains, we compared two mTMS designs (5-channel planar and 6/12-channel spherical systems) with standard sTMS figure-of-eight coils through E-field simulations. Three complementary metrics quantified stimulation quality: Focality, Target2Max, and OverstimulatedArea. ResultsDespite using a single optimized placement for all region-of-interest targets, mTMS achieved focality comparable to repositioned single-channel TMS in this in-silico study. For superficial targets, single-channel TMS showed slightly better stimulation, but for deeper cortical targets (>25 mm skin-cortex distance), mTMS performed similarly. More mTMS channels improved focality but required stronger current-rate constraints. The planar design performed better for deeper targets, while spherical designs improved with additional channels. ConclusionmTMS systems demonstrate remarkable performance comparable to standard TMS, enabling efficient multi-target stimulation without repositioning. Our open-source framework provides practical tools for designing and evaluating mTMS systems, supporting goal-directed mTMS development and effective application.

neuroscience↗

bioRxiv2025

Not two sides of the same coin: Divergent effects of motor state on corticospinal and cortical responses to TMS of motor cortex

BackgroundTranscranial magnetic stimulation (TMS) of the motor cortex can elicit motor evoked potentials (MEPs) in target muscles, reflecting corticospinal excitability. MEP amplitudes increase with TMS intensity and can be facilitated by tonic muscle pre-activation. Since conventional transcranial evoked potentials (TEPs) also grow with increasing TMS intensity, cortical and corticospinal responses are often considered two facets of the same process. If this were true, changes in physiological motor state should modulate TEPs and MEPs in a similar manner. MethodsTo compare the state-dependency of cortical and corticospinal responses to single-pulse TMS, we simultaneously recorded TEPs and MEPs in 16 healthy young adults during relaxation and isometric contraction of the right first dorsal interosseous (FDI) muscle. For each condition, 100 biphasic TMS pulses were delivered to the left primary motor hand area at five different intensities centered around the resting motor threshold. ResultsTEP and MEP amplitudes increased with stimulation intensity. As predicted, tonic muscle contraction consistently facilitated MEP. On the contrary, muscle contraction attenuated two key peaks of the TEP (N15 and N100). The state-dependent effects of corticospinal and cortical responses were not correlated. DiscussionBoth TEPs and MEPs are reliably modulated by motor state, yet they differ in direction and their magnitudes do not scale with each other. These findings challenge the assumption that cortical and corticospinal responses are two aspects of the same process. MEP facilitation during contraction likely reflects increased spinal excitability, whereas TEP attenuation may reflect reduced responsiveness of cortico-cortical or cortico-subcortical networks.

neuroscience↗

bioRxiv2025

Single pointwise samples of electric field on a neuron model cannot predict activation threshold by brain stimulation

BackgroundSome computational models of neural activation by transcranial magnetic stimulation overestimate the electric field (E-field) threshold compared to in vivo measurements. A recent study proposed a statistical method to account for the influence of microscopic perturbations to the E-field. The method, however, relies on the unsubstantiated assumption that thresholds can be predicted by single pointwise samples of the E-field strength along neural cables. ObjectiveWe analyzed neural responses to E-field with microscopic perturbations and demonstrate via theoretical derivation and simulations that neural activation is not determined by pointwise E-field amplitude but rather by spatial integration of the E-field along the neural cable. Therefore, the influence of microscopic E-field perturbations is negligible due to the spatiotemporal filtering by the neural membrane and axoplasm. MethodsWe derive the axial and transmembrane currents in a neural cable for an imposed E-field with microscopic perturbations. We simulate neural activation thresholds of unmyelinated and myelinated axons in two stimulation scenarios and compare thresholds for E-field activation with and without perturbations. ResultsIn the theoretical derivation, the perturbation terms average out to zero on larger spatial scales indicating that they do not influence neural activation thresholds. Simulated thresholds with the E-field spatial perturbations present had negligible differences (< 3.4%) compared to those without. ConclusionSingle point samples of the microscopic E-field on a neural cable cannot predict neural activation thresholds. Neural simulations should be used to determine any influence of the E-field spatial perturbations. The latter, however, are unlikely to account for the difference between experimental and simulated E-field thresholds.

bioengineering↗

bioRxiv2025

Dual-site beta transcranial alternating current stimulation during a bimanual coordination task modulates functional connectivity between motor areas

BackgroundCommunication within brain networks depends on functional connectivity. One promising approach to modulate such connectivity between cortical areas is dual-site transcranial alternating current stimulation (tACS), which non-invasively applies weak alternating currents to two brain areas. Objectives/HypothesesIn the current study, we aimed to modulate inter-regional functional connectivity with dual-site tACS to bilateral primary motor cortices (M1s) during bimanual coordination and, in turn, alter behaviour. MethodsUsing functional magnetic resonance imaging (fMRI), we recorded participants brain responses during a bimanual coordination task in a concurrent tACS-fMRI design. While performing a slow and fast version of the task, participants received one of three types of beta (20 Hz) dual-site tACS over both M1s: in-phase, jittered-phase or sham, in a within-subject, repeated measures design. ResultsWhile we did not observe any significant tACS effects on behaviour, the study revealed a disruptive effect of in-phase tACS on interhemispheric connectivity. Additionally, the two active types of tACS (in-phase and jittered-phase) differed in the task-related M1 connectivity with other motor cortical regions, such as premotor cortex and supplementary motor area. Furthermore, individual E-field strengths were related to functional connectivity in the in-phase condition. ConclusionsDual-site beta tACS over both M1s altered functional connectivity between motor areas. However, this effect did not translate to the behavioural level, possibly due to compensatory mechanisms. HighlightsO_LIInterhemispheric connectivity between the primary motor cortices was targeted with dual-site beta tACS during bimanual coordination. C_LIO_LIIn-phase as compared to sham tACS disrupted interhemispheric connectivity during task performance. C_LIO_LIIn-phase and jittered-phase tACS led to different task-related functional connectivity patterns within the motor network. C_LIO_LIThe relationship between individual in-phase E-field strengths and interhemispheric connectivity depended on task demand. C_LIO_LIThere were no significant tACS effects on behavioural performance of bimanual coordination, possibly due to compensatory mechanisms. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=143 SRC="FIGDIR/small/647211v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@17ecdd8org.highwire.dtl.DTLVardef@1fc5b25org.highwire.dtl.DTLVardef@c3df42org.highwire.dtl.DTLVardef@17671bb_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2025

Rostro-caudal TMS mapping of immediate transcranial evoked potentials reveals a pericentral crescendo-decrescendo pattern

BackgroundWe recently demonstrated that single-pulse TMS of the primary sensorimotor hand area (SM1HAND) elicits an immediate transcranial evoked potential (iTEP). This iTEP response appears within 2-7 ms post-TMS, featuring high-frequency peaks superimposed on a slow positive wave. Here, we used a linear TMS-EEG mapping approach to characterize the rostro-caudal iTEP expression and compared it to that of motor-evoked potentials (MEPs). MethodsIn 15 healthy young volunteers (9 females), we identified the iTEP hotspot in left SM1HAND. We applied single biphasic TMS pulses at an intensity of 110% of resting motor threshold over six cortical sites along a rostro-caudal axis (2 cm rostral to 3 cm caudal to the SM1HAND hotspot). We analyzed site-specific iTEP and MEP responses. ResultsiTEP magnitude decreased rostrally and caudally from the SM1HAND hotspot. MEPs exhibited a similar rostro-caudal crescendo-decrescendo pattern. While iTEP and MEP response profiles were similar, normalized iTEP amplitudes decayed less rapidly at the first postcentral site. DiscussionThese findings support the idea that pericentral iTEPs reflect a direct response signature of the pericentral cortex, possibly involving a synchronized TMS-induced excitation of cortical pyramidal tract neurons. Similar but non-identical rostro-caudal patterns suggest that iTEPs and MEPs may arise from overlapping but distinct neuronal populations.

neuroscience↗

bioRxiv2024

Personalized electric field simulations of deformable large TMS coils based on automatic position and shape optimization

BackgroundTranscranial Magnetic Stimulation (TMS) therapies use both focal and unfocal coil designs. Unfocal designs often employ bendable windings and moveable parts, making realistic simulations of their electric fields in inter-individually varying head sizes and shapes challenging. This hampers comparisons of the various coil designs and prevents systematic evaluations of their dose-response relationships. ObjectiveIntroduce and validate a novel method for optimizing the position and shape of flexible coils taking individual head anatomies into account. Evaluate the impact of realistic modeling of flexible coils on the electric field simulated in the brain. MethodsAccurate models of four coils (Brainsway H1, H4, H7; MagVenture MST-Twin) were derived from computed tomography data and mechanical measurements. A generic representation of coil deformations by concatenated linear transformations was introduced and validated. This served as basis for a principled approach to optimize the coil positions and shapes, and to optionally maximize the electric field strength in a region of interest (ROI). ResultsFor all four coil models, the new method achieved configurations that followed the scalp anatomy while robustly preventing coil-scalp intersections on N=1100 head models. In contrast, setting only the coil center positions without shape deformation regularly led to physically impossible configurations. This also affected the electric field calculated in the cortex, with a median peak difference of [~]16%. In addition, the new method outperformed grid search-based optimization for maximizing the electric field of a standard figure 8 coil in a ROI with a comparable computational complexity. ConclusionOur approach alleviates practical hurdles that so far hampered accurate simulations of bendable coils. This enables systematic comparison of dose-response relationships across the various coil designs employed in therapy. HighlightsO_LIautomatic positioning and shape optimization of large deformable TMS coils C_LIO_LIensures adherence to the head anatomy and prevents coil-head intersections C_LIO_LIenable automatic electric field maximization in target brain regions C_LIO_LIoutperforms grid search for standard flat coils C_LIO_LIprovides accurate computational models of four coils used in clinical practice C_LI

neuroscience↗

bioRxiv2024

A Leadfield-Free Optimization Framework for Transcranially Applied Electric Currents

BackgroundTranscranial Electrical Stimulation (TES), Temporal Interference Stimulation (TIS), Electroconvulsive Therapy (ECT) and Tumor Treating Fields (TTFields) are based on the application of electric current patterns to the brain. ObjectiveThe optimal electrode positions, shapes and alignments for generating a desired current pattern in the brain vary between persons due to anatomical variability. The aim is to develop a flexible and efficient computational approach to determine individually optimal montages based on electric field simulations. MethodsWe propose a leadfield-free optimization framework that allows the electrodes to be placed freely on the head surface. It is designed for the optimization of montages with a low to moderate number of spatially extended electrodes or electrode arrays. Spatial overlaps are systematically prevented during optimization, enabling arbitrary electrode shapes and configurations. The approach supports maximizing the field intensity in target region-of-interests (ROI) and optimizing for a desired focality-intensity tradeoff. ResultsWe demonstrate montage optimization for standard two-electrode TES, focal center-surround TES, TIS, ECT and TTFields. Comparisons against reference simulations are used to validate the performance of the algorithm. The system requirements are kept moderate, allowing the optimization to run on regular notebooks and promoting its use in basic and clinical research. Conclusion(s)The new framework complements existing optimization methods that require small electrodes, a predetermined discretization of the electrode positions on the scalp and work best for multi-channel systems. It strongly extends the possibilities to optimize electrode montages towards application-specific aims and supports researchers in discovering innovative stimulation schemes. The framework is available in SimNIBS.

neuroscience↗

bioRxiv2024

Fast FEM-based Electric Field Calculations for Transcranial Magnetic Stimulation

ObjectiveTo provide a Finite-Element Method (FEM) for rapid, repeated evaluations of the electric field induced by transcranial magnetic stimulation (TMS) in the brain for changing coil positions. ApproachPreviously, we introduced a first-order tetrahedral FEM enhanced by super- convergent patch recovery (SPR), striking a good balance between computational efficiency and accuracy (Saturnino et al 2019 J. Neural Eng. 16 066032). In this study, we refined the method to accommodate repeated simulations with varying TMS coil position. Starting from a fast direct solver, streamlining the pre- and SPR-based post-calculation steps using weight matrices computed during initialization strongly improved the computational efficiency. Additional speedups were achieved through efficient multi-core and GPU acceleration, alongside the optimization of the volume conductor model of the head for TMS. Main ResultsFor an anatomically detailed head model with [~]4.4 million tetrahedra, the optimized implementation achieves update rates above 1 Hz for electric field calculations in bilateral gray matter, resulting in a 60-fold speedup over the previous method with identical accuracy. An optimized model without neck and with adaptive spatial resolution scaled in dependence to the distance to brain grey matter, resulting in [~]1.9 million tetrahedra, increased update rates up to 10 Hz, with [~]3% numerical error and [~]4% deviation from the standard model. Region-of-interest (ROI) optimized models focused on the left motor, premotor and dorsolateral prefrontal cortices reached update rates over 20 Hz, maintaining a difference of <4% from standard results. Our approach allows efficient switching between coil types and ROI during runtime which greatly enhances the flexibility. SignificanceThe optimized FEM enhances speed, accuracy and flexibility and benefits various applications. This includes the planning and optimization of coil positions, pre-calculation and training procedures for real-time electric field simulations based on surrogate models as well as targeting and dose control during neuronavigated TMS.

neuroscience↗

bioRxiv2024

Head And Shoulders - The Impact Of An Extended Head Model On The Simulation And Optimization Of Transcranial Electric Stimulation

Electric field calculations are increasingly used for dose characterization of transcranial electrical stimulation (tES), but existing open-source head models are inaccurate for extracephalic montages that include electrodes placed on the neck or shoulder. We introduce the "Ernie Extended" model, an MRI- and CT-derived open-source head model extending to the upper shoulder region. Simulations of extracephalic tES targeting the cerebellum and supplementary motor area show significant differences in electric fields when using Ernie Extended compared to the non-extended Ernie model. Additionally, we propose an electrode layout that complements the electroencephalography 10- 20 system with extracephalic electrode positions. We demonstrate the use of this layout for optimizing multi-electrode tES montages for cerebellar stimulation, enhancing focality and reducing off-target stimulation, particularly of the spinal cord. Our results highlight the practical value of the Ernie Extended model for accurately characterizing doses produced by extracephalic tES montages and when targeting more caudal brain regions.

neuroscience↗

bioRxiv2023

Transcranial magnetic stimulation of primary motor cortex elicits a site-specific immediate transcranial evoked potential

BackgroundTranscranial evoked potentials (TEPs) measured via electroencephalography (EEG) are widely used to study the cortical responses to transcranial magnetic stimulation (TMS). Immediate transcranial evoked potentials (i-TEPs) have been obscured by pulse and muscular artifacts. Thus, the TEP peaks that are commonly reported have latencies that are too long to be caused by direct excitation of cortical neurons. MethodsIn 14 healthy individuals, we recorded i-TEPs evoked by a single biphasic TMS pulse targeting the primary motor hand area (M1HAND) or parietal or midline control sites. Sampling EEG at 50 kHz enabled us to reduce the duration of the TMS pulse artifact to a few milliseconds, while minor adjustments of the TMS coil tilt or position enabled us to avoid cranial muscular twitches during the experiment. ResultsWe observed an early positive EEG deflection starting after approx. 2 ms combined with a series of peaks with an inter-peak interval of [~]1.1-1.4 ms in electrodes overlying the stimulated sensorimotor region. This multi-peak i-TEP response was only evoked by TMS of the M1HAND region and was modified by changes in stimulation intensity and current direction. DiscussionSingle-pulse TMS of the M1HAND evokes an immediate local multi-peak response at the cortical site of stimulation. Our results suggest that the observed i-TEP patterns are genuine cortical responses evoked by TMS caused by synchronized excitation of pyramidal neurons in the targeted precentral cortex. This notion needs to be corroborated in future studies, including further investigations into the potential contribution of instrumental or physiological artifacts.

neuroscience↗

bioRxiv2023

Directional Sensitivity of Cortical Neurons Towards TMS Induced Electric Fields

We derived computationally efficient average response models of different types of cortical neurons, which are subject to external electric fields from Transcranial Magnetic Stimulation. We used 24 reconstructions of pyramidal cells (PC) from layer 2/3, 245 small, nested, and large basket cells from layer 4, and 30 PC from layer 5 with different morphologies for deriving average models. With these models, it is possible to efficiently estimate the stimulation thresholds depending on the underlying electric field distribution in the brain, without having to implement and compute complex neuron compartment models. The stimulation thresholds were determined by exposing the neurons to TMS-induced electric fields with different angles, intensities, pulse waveforms, and field decays along the somato-dendritic axis. The derived average response models were verified by reference simulations using a high-resolution realistic head model containing several million neurons. Differences of only 1-2% between the average model and the average response of the reference cells were observed, while the computation time was only a fraction of a second compared to several weeks using the cells. Finally, we compared the model behavior to TMS experiments and observed high correspondence to the orientation sensitivity of motor evoked potentials. The derived models were compared to the classical cortical column cosine model and to simplified ball-and-stick neurons. It was shown that both models oversimplify the complex interplay between the electric field and the neurons and do not adequately represent the directional sensitivity of the different cell types. The derived models are simple to apply and only require the TMS induced electric field in the brain as input variable. The models and code are available to the general public in open-source repositories for integration into TMS studies to estimate the expected stimulation thresholds for an improved dosing and treatment planning in the future.

neuroscience↗