Biology subjects

Deng, Z.-D.

Publications and source records attributed to Deng, Z.-D..

At least 19 recordsLinked to original sources

bioRxiv2026

Accurate Hippocampal Electric Field Modeling for Electroconvulsive Therapy: Numerical Accuracy and Convergence

Accurate hippocampal electric field (E-field) prediction is important for individualized electroconvulsive therapy (ECT) dosing and emerging deep-brain stimulation approaches such as temporal interference. Because hippocampal fields are far weaker than those beneath the stimulation electrodes, they are highly sensitive to tissue interfaces, conductivity contrasts, and numerical discretization, so numerical error can rival the physical uncertainties of anatomy and conductivity. We investigate this numerical component of hippocampal dosimetry using individualized head models from eleven ECT patients. Identical head40 segmentations, comprising 40 tissue compartments including the bilateral hippocampi, were simulated with three independent numerical methods: a charge-based boundary-element fast multipole method (BEM-FMM), a voxel-based hexahedral finite-element solver, and a conformal tetrahedral finite-element solver. For each, resolution was increased systematically and convergence assessed from the average hippocampal E-field magnitude. At the highest attainable resolutions, the three methods agreed closely, differing by 6%-7% in the left hippocampus and 9%-12% in the right. At default or coarse resolutions, however, they disagreed by 28.8% on average and up to 50.3% in the right hippocampus. Numerical convergence should therefore be established before differences are attributed to anatomical or conductivity uncertainty, and independent-solver agreement provides a practical basis for reliable hippocampal dosimetry.

neuroscience↗

bioRxiv2026

A reactivated thalamocortical plasticity window promotes learning and is reshaped by experience

Adult sensory loss can reactivate critical-period-like thalamocortical plasticity, but whether this reactivation defines a temporally gated circuit state that facilitates learning and is reciprocally shaped by experience remains unknown. Here we define its in vivo trajectory and functional consequences in adult mouse barrel cortex. Infraorbital nerve transection opened a transient window of enhanced layer 4 thalamocortical gain. Training during this window lowered whisker-detection thresholds and promoted learning by accelerating the transition to stable performance. Local GluN2B blockade prevented both cortical potentiation and the learning advantage, linking critical-period-associated plasticity mechanisms to adaptive behavior in the adult brain. Neuropixels recordings showed that weak inputs preferentially increased neuronal responses, whereas strong inputs produced sharper temporal coding. The relationship was reciprocal: experience reshaped the trajectory of this circuit state, with training before the normal peak advancing the emergence of potentiation, training during the active window prolonging the potentiated state, and training after closure failing to reinstate potentiation. State prolongation accompanied more persistent sensory memory. These findings establish a reciprocal, timing-dependent interaction between endogenous plasticity and experience, revealing a general principle by which adult circuits can convert transient plastic potential into adaptive behavioral change and informing strategies that align training with periods of heightened plasticity.

neuroscience↗

bioRxiv2026

Low Intensity Multi-Channel Steering TMS Array for Network Level Neuromodulation

Objective: Low-intensity transcranial magnetic stimulation (LI-TMS) is being investigated as a gel-free alternative to transcranial electrical stimulation (tES), but existing systems remain almost exclusively single-channel and cannot electronically steer the induced electric field. We present the design, modeling, and experimental measurement of a wearable whole-head, multichannel, steerable LI-TMS array. Methods: The system comprises a 102-channel conformal coil array with independently controlled drivers capable of arbitrary waveform synthesis, together with a boundary element fast multipole method (BEM-FMM) framework that computes the coil currents required to produce prescribed cortical field patterns. A 12-channel prototype was characterized by coil-current, electric-field, and thermal measurements. Results: The prototype produced a peak primary electric field of approximately 1 V/m measured in air 4 cm from the inner helmet surface. Whole-array modeling attained cortical fields of up to 1.5 V/m, reproduced the field distribution of a clinically validated low-intensity stimulator to within 3%-5%, and demonstrated focal targeting of the dorsolateral prefrontal cortex, simultaneous delivery of electric field to the default mode network nodes, and synthesis of electric fields following the traveling alpha wave. Conclusion: Electronically steerable, whole-head LI-TMS is feasible using accessible microprocessor-controlled power electronics. Significance: The array reaches the cortical field regime of tES without scalp contact or the associated shunting of current through the scalp, offering a route to testing network-level, phaselocked weak-field neuromodulation.

bioengineering↗

bioRxiv2026

Model-based assessment of race, sex, and electrode montage in ECT

Objective: This computational modeling study quantified the influence of sex and race-related cranial anatomy on predicted brain-wide current flow during electroconvulsive therapy (ECT) across conventional (bifrontal (BF), bitemporal/bilateral (BL), right unilateral (RUL)) and experimental (focal electrically administered seizure therapy (FEAST) and frontomedial (FM)) electrode montages. The objective was to determine whether race-associated variability meaningfully contributes to differences in ECT stimulation metrics across montages. Methods: Finite element head models of Chinese, Black, and Caucasian subjects were developed using high-resolution magnetic resonance imaging and analyzed using the Realistic vOlumetric- Approach-based Stimulator for Transcranial electric stimulation (ROAST) pipeline (N = 150 total; n = 50 per cohort, comprising 25 M and 25 F, age range: 20-30 years). Five ECT montages were simulated under a constant-current condition (900mA). Stimulation strength (Ebrain/Eth) was quantified as 90th percentile of brain-wide E-field magnitude (Ebrain) relative to neuronal activation threshold (Eth = 0.25 V/cm) quantified stimulation strength. Overall focality was evaluated as a percentage of brain volume stimulated above the neural activation threshold (Ebrain [≥] Eth), while laterality was quantified as the median right-to-left hemispheric E-field magnitude ratio. The effects of race, sex, and montage on stimulation strength, focality, and hemispheric laterality were statistically analyzed. Results: Substantial race- and sex-related differences observed in cranial anatomy resulted in systematic variation in predicted ECT-induced E-field intensity. Brain-wide E-field magnitude varied by both race and montage, with the largest fields generally observed in Caucasian head models and during BL stimulation. Montage exerted the strongest effect on stimulation strength (Ebrain/Eth) with BL and FEAST producing the highest stimulation strengths, followed by RUL and FM, while BF produced the lowest. Caucasian subjects generally predicted higher stimulation strengths than Black and Chinese subjects, whereas females predicted modestly higher stimulation strengths than males. Laterality was primarily determined by montage, with FEAST producing the greatest hemispheric asymmetry, followed by RUL. Chinese subjects demonstrated higher laterality ratios than both Black and Caucasian subjects. BL, RUL, and FEAST stimulated substantially larger brain volumes above neural activation threshold (less focal stimulation) than BF. Lower focality was observed in Caucasian subjects relative to Black and Chinese subjects, and in females relative to males. Conclusions: Electrode montage was the primary determinant of predicted ECT stimulation strength, focality, and laterality. Race-related anatomical differences and, to a lesser extent, sex-related differences systematically altered stimulation patterns, supporting consideration of individualized anatomy in ECT dosing and treatment optimization.

neuroscience↗

bioRxiv2026

Direct Reconstruction of DC Cortical Conductivity from Large-Scale Electron Microscopy Data

Electrical conductivity of cortical gray matter governs the magnitude and spatial distribution of electric fields generated by brain stimulation and intrinsic neuronal activity measured with M/EEG and intracortical recordings. However, reported macroscopic conductivity values vary by more than threefold, limiting the fidelity of bioelectromagnetic models and leaving unresolved whether this variability reflects measurement uncertainty or genuine structural heterogeneity of cortical tissue. Here, we present a multiscale computational framework that, for the first time, attempts to derive mesoscale conductivity maps of mouse visual cortex at 50-{micro}m resolution directly from large-volume, segmented nanometer-scale electron microscopy data. The Minnie 65 subvolume of the MICrONS dataset is accurately subdivided into 1,224 50-{micro}m cubic blocks. Each block contains, on average, 40-50 million membrane facets of a highly convoluted and dense cellular structure. Three orthogonal electrode pairs are applied to each isolated block to estimate the three principal components of the conductivity tensor. Quasistatic electric modeling is enabled by an iterative boundary-element fast multipole method (BEM-FMM) under the approximation of non-conducting membranes (DC conductivity). Spatially averaged conductivity values predicted by our framework agree well with prior low-resolution measurements in rats, validating the approach. At the same time, the resulting mesoscale maps reveal pronounced conductivity granularity at 50-100 {micro}m scales as well as significant variations in both radial and tangential directions. These results indicate that mesoscale conductivity heterogeneity could be an intrinsic structural property of the cortex. Limitations and extensions of this study are discussed in detail.

neuroscience↗

bioRxiv2026

Charge Based Boundary Element Method with Residual Driven Adaptive Mesh Refinement for High Resolution Electrical Simulation Modeling

Accurate transcranial electrical stimulation (TES), electroconvulsive therapy (ECT), and electroencephalography (EEG) forward modeling requires resolving numerical singularities in the charge density near electrodes and tissue interfaces. We present an adaptive mesh refinement (AMR) strategy for the charge based boundary element method (BEM) accelerated by the fast multiple method (BEM-FMM) including electrode and interface singularities. We derive a new error estimator which considers both local and nonlocal contributions of the single-layer potential operator and construct a refinement criterion based on the difference in charge solution across AMR iterations. We evaluate this approach on a 5-layer sphere model and on multiple subject-specific head models derived from the 7-tissue SimNIBS (headreco) and 40-tissue Sim4Life (head40) segmentations, using both voltage-controlled and current-controlled electrode formulations. Through convergence analysis on the white matter and deep hippocampal targets, we find electric fields with relative residual errors below 0.1% and 1% for SimNIBS and Sim4Life models, respectively. Our results indicate that the residual based AMR applied to BEM-FMM leads to numerically stable TES and EEG forward solutions in realistic head models.

neuroscience↗

bioRxiv2026

Are Synaptic Clefts Directionally Oriented?

Synapses are fundamental building blocks of cortical circuits, yet their geometry is typically regarded as a local property, independent of mesoscale architecture. The prevailing assumption is that synaptic clefts are isotropically oriented in space. Here, we test this assumption by analyzing approximately 117 million synaptic clefts from two independent 1 mm3 electron microscopy datasets: the human H01 middle temporal gyrus and the mouse MICrONS primary visual cortex, using three independent cleft-extraction methods. Across both volumes, we observe that synaptic cleft orientations are not randomly distributed, but instead show statistically significant and spatially coherent directional biases across cortical layers. This mesoscale anisotropy is conserved across species, yet is stronger and more consistent in human association cortex than in mouse sensory cortex, a difference that may reflect the expanded dendritic arbors and greater integrative demands of human pyramidal neurons. We propose that cleft orientation bias is a geometric consequence of the axonal and dendritic architecture that shapes synapse formation, representing a new candidate organizational feature of cortical microarchitecture with potential implications for circuit computation and neuromodulation. These findings motivate targeted physiological studies to determine whether synaptic orientation contributes causally to cortical function.

neuroscience↗

bioRxiv2026

Assessing suitability of ultra-low-field MRI for TES electric field models

ObjectiveRecent ultra-low-field (ULF) MRI systems provide an option for more accessible and cost-effective imaging to widely used higher field (HF, usually 3T) systems. However, it remains uncertain whether ULF scans can be used for reliable TES current-flow modeling as opposed to using 3T MRI. MethodsWe used raw anatomical scans of 23 healthy adults from 64 mT and 3T systems. We enhanced the 64 mT scans using SynthSR. Using our established current-flow modeling pipeline we determined the electric fields (EF) for the ULF and 3T scans induced by the classic M1-SO electrode montage. We quantified the differences in EF at three regions of interest (ROI): left motor cortex (LMC), anterior commissure (AC), and left hippocampus (LHC). ResultsAt the cortical ROI (LMC), the individual mean EF based on a 3T scan was found to be 27% higher than the corresponding ULF scan. The average mean relative error was found to be 40%. At AC, the individual mean EF based on a 3T scan continued to be elevated by about 13% in magnitude with respect to the corresponding ULF scan with a mean error range of 31-34%. At LHC, comparison of the induced individual mean EF magnitudes indicated no clear bias between 3T-based and ULF-based models. The average mean relative error at this level dropped to [~]20%. DiscussionThe substantial decrease in cortical EF when using an ULF scan is predominantly explained by the overestimation of cerebrospinal fluid (CSF) noted by prior morphological comparison studies. Scaling up EF magnitude to match predicted cortical values to a 3T scan may be considered depending on the modeling question being addressed. While preliminary, our results suggest an "equalizing" effect between ULF and 3T predictions with increasing depth within the brain.

bioengineering↗

bioRxiv2025

Improved Source Localization of Auditory Evoked Fields using Reciprocal BEM-FMM

The precise localization of auditory evoked fields (AEFs) from magnetoencephalography (MEG) data is very important for the functional understanding of the auditory cortex in medicine and cognitive neuroscience. The numerical solution of the field equations in the human head using the boundary element method (BEM) is a powerful tool for achieving this. We hypothesized that the spatial resolution of the BEM is crucial for the achievable accuracy. However, in classical BEM (as implemented, e.g., in MNE-Python), very high resolutions are impractical due to the associated prohibitive computational effort. In contrast, our recently introduced reciprocal boundary element fast multipole method (reciprocal BEM-FMM) allows for hitherto unprecedented spatial resolution. In this work, we apply our reciprocal BEM-FMM technique for source estimation to localize AEFs, and we compare our results with the source estimates produced using a 3-layer BEM model (standard BEM) via MNE-Python. We first validate our methodology through comparison of source estimates of simulated N1m components of AEFs using a receiver operating characteristic (ROC) measure. While we obtain ROC measures of about 80% for the standard BEM, reciprocal BEM-FMM reaches about 90%, a significant statistical improvement. We then apply this methodology to analyze the source estimates of experimental data obtained from a cohort of 7 participants subjected to binaural auditory stimulation. Using a dispersion measurement to quantify the focality of localized sources, we find improvements upwards of 30% using reciprocal BEM-FMM over the standard BEM. Analyses from both simulated and experimental data show localization of AEFs using high-resolution reciprocal BEM-FMM is significantly better in terms of accuracy and focality than those estimates of the low-resolution standard BEM. We therefore recommend using the high-resolution reciprocal BEM-FMM to utilize high spatial anatomical precision for the modeling of neural activity.

neuroscience↗

bioRxiv2025

Controllability analysis of macaque structural connectome from an edge centric perspective

In this paper, we investigate the edge controllability properties of the macaque structural connectome, which is reconstructed using optimal tractography parameters. We derive the expression of edge modal controllability and edge average controllability, providing a mathematical framework to analyze their roles from a network systems perspective. Further, we establish the relationship between the two controllability measures, providing insights into their functional implications. We also identify the top edges with the highest average controllability values, which may be critical in facilitating state transitions within the macaque brain network. These findings may have implications for neurostimulation interventions.

neuroscience↗

bioRxiv2024

Optimal Frequency for Seizure Induction with Electroconvulsive Therapy and Magnetic Seizure Therapy

Electroconvulsive therapy (ECT) and magnetic seizure therapy (MST) are effective in the treatment of medication-resistant depression. Determining the stimulus frequency resulting in the lowest seizure threshold could produce fewer adverse effects by reducing the overall stimulus intensity. To determine the optimal frequency for seizure induction, four male rhesus macaques were titrated with an increasing number of pulses at fixed frequencies ranging from 5 to 240 pulses per second (pps) using ultrabrief-pulse right-unilateral ECT and circular-coil-on-vertex MST. The seizure threshold dependence on stimulus frequency was similar for ECT and MST. While higher frequencies required progressively shorter trains to induce a seizure, the middle frequency range was associated with the fewest pulses (and hence the least charge and energy), with a minimum at 16 pps and similarly low thresholds for 10 and 25 pps. The number of pulses at seizure threshold increased markedly at lower and higher frequencies. The lowest stimulus frequencies, 5 and 10 pps, were associated with the greatest ictal power measured by electroencephalography. While this study did not assess efficacy or side effects, the results highlight the significance of stimulus frequency for seizure induction, suggest efficient titration schedules that minimize exposure to the electrical stimulus, and can inform studies to assess the impact on clinical outcomes.

bioengineering↗

bioRxiv2024

Electromagnetic Modeling within a Microscopically Realistic Brain - Implications for Brain Stimulation

Modeling brain stimulation at the microscopic scale may reveal new paradigms for various stimulation modalities. We present the largest map to date of extracellular electric field distributions within a layer L2/L3 mouse primary visual cortex brain sample. This was enabled by the automated analysis of serial section electron microscopy images with improved handling of image defects, covering a volume of 250 x 140 x 90 m3. The map was obtained by applying a uniform brain stimulation electric field at three different polarizations and accurately computing microscopic field perturbations using the boundary element fast multipole method. We used the map to identify the effect of microscopic field perturbations on the activation thresholds of individual neurons. Previous relevant studies modeled a macroscopically homogeneous cortical volume. Our result shows that the microscopic field perturbations - an electric field spatial noise with a mean value of zero - only modestly influence the macroscopically predicted stimulation field strengths necessary for neuronal activation. The thresholds do not change by more than 10% on average. Under the stated limitations and assumptions of our method, this result justifies the conventional theory of "invisible" neurons embedded in a macroscopic brain model for transcranial magnetic and transcranial electrical stimulation. However, our result is solely sample-specific and largely neglects the effect of the microcapillary network. Furthermore, we only considered the uniform impressed field and a single- pulse stimulation time course. Significance statementThis study is arguably the first attempt to model brain stimulation at the microscopic scale, enabled by automated analysis of modern scanning electron microscopy images of the brain. It concentrates on modeling microscopic perturbations of the extracellular electric field caused by the physical cell structure and is applicable to any type of brain stimulation. Data availability statementPost-processed cell CAD models (383, stl format), microcapillary CAD models (34, stl format), post-processed neuron morphologies (267, swc format), extracellular electric field and potential distributions at different polarizations (267x3, MATLAB format), *.ses projects files for biophysical modeling with Neuron software (267x2, Neuron format), and computed neuron activating thresholds at different conditions (267x8, Excel tables, without the sample polarization correction from Section 2.8) are made available online through BossDB, a volumetric open-source database for 3D and 4D neuroscience data.

neuroscience↗

bioRxiv2024

Bayesian Optimization of Neurostimulation (BOONStim)

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

neuroscience↗

bioRxiv2023

Real-Time Computation of Brain E-Field for Enhanced Transcranial Magnetic Stimulation Neuronavigation and Optimization

Transcranial Magnetic Stimulation (TMS) coil placement and pulse wave-form current are often chosen to achieve a specified E-field dose on targeted brain regions. TMS neuronavigation could be improved by including real-time accurate distributions of the E-field dose on the cortex. We introduce a method and develop software for computing brain E-field distributions in real-time enabling easy integration into neuronavigation and with the same accuracy as 1st-order finite element method (FEM) solvers. Initially, a spanning basis set (< 400) of E-fields generated by white noise magnetic currents on a surface separating the head and permissible coil placements are orthogonalized to generate the modes. Subsequently, Reciprocity and Huygens principles are utilized to compute fields induced by the modes on a surface separating the head and coil by FEM, which are used in conjunction with online (real-time) computed primary fields on the separating surface to evaluate the mode expansion. We conducted a comparative analysis of E-fields computed by FEM and in real-time for eight subjects, utilizing two head model types (SimNIBSs headreco and mri2mesh pipeline), three coil types (circular, double-cone, and Figure-8), and 1000 coil placements (48,000 simulations). The real-time computation for any coil placement is within 4 milliseconds (ms), for 400 modes, and requires less than 4 GB of memory on a GPU. Our solver is capable of computing E-fields within 4 ms, making it a practical approach for integrating E-field information into the neuronavigation systems without imposing a significant overhead on frame generation (20 and 50 frames per second within 50 and 20 ms, respectively). O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=96 SRC="FIGDIR/small/564044v1_fig8.gif" ALT="Figure 8"> View larger version (27K): org.highwire.dtl.DTLVardef@1520141org.highwire.dtl.DTLVardef@d05835org.highwire.dtl.DTLVardef@4f1aa9org.highwire.dtl.DTLVardef@15f7b90_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 8:C_FLOATNO Mean computational time for pre-processing stage (mode and field generation stage) for mri2mesh models (A) and headreco models (B). At any rank (mode), the time is calculated across 8 head models from 8 subjects.) C_FIG

bioengineering↗

bioRxiv2023

Software Package for Transcranial Magnetic Stimulation Coil and Coil Array Analysis and Design

ObjectiveThis study aims to describe a MATLAB software package for transcranial magnetic stimulation (TMS) coil analysis and design. ApproachElectric and magnetic fields of the coils as well as their self- and mutual (for coil arrays) inductances are computed, with or without a magnetic core. Solid and stranded (Litz wire) conductors are also taken into consideration. The starting point is the centerline of a coil conductor(s), which is a 3D curve defined by the user. Then, a wire mesh and a computer aided design (CAD) mesh for the volume conductor of a given cross-section (circular, elliptical, or rectangular) are automatically generated. Self- and mutual inductances of the coil(s) are computed. Given the conductor current and its time derivative, electric and magnetic fields of the coil(s) are determined anywhere in space. Computations are performed with the fast multipole method (FMM), which is the most efficient way to evaluate the fields of many elementary current elements (current dipoles) comprising the current carrying conductor at a large number of observation points. This is the major underlying mathematical operation behind both inductance and field calculations. Main ResultsThe wire-based approach enables precise replication of even the most complex physical conductor geometries, while the FMM acceleration quickly evaluates large quantities of elementary current filaments. Agreement to within 0.74% was obtained between the inductances computed by the FMM method and ANSYS Maxwell 3D for the same coil model. Although not provided in this study, it is possible to evaluate non-linear magnetic cores in addition to the linear core exemplified. An experimental comparison was carried out against a physical MagVenture C-B60 coil; the measured and simulated inductances differed by only 1.25%, and nearly perfect correlation was found between the measured and computed E-field values at each observation point. SignificanceThe developed software package is applicable to any quasistatic inductor design, not necessarily to the TMS coils only.

neuroscience↗

bioRxiv2023

An Adaptive H-Refinement Method for the Boundary Element Fast Multipole Method for Quasi-static Electromagnetic Modeling

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

neuroscience↗

bioRxiv2022

Augmenting Transcranial Magnetic Stimulation Coil with Magnetic Material: An Optimization Approach

Transcranial magnetic stimulation (TMS) is a neuromodulation technique that has been approved by the U.S. Food and Drug Administration for several neuropsychiatric disorders, including major depression and obsessive-compulsive disorder. However, the therapeutic efficacy of TMS treatment has been modest, despite decades of research. While there are many potential reasons as to why, one of the most obvious is the limitations of current technologies. One prominent example is the penetration depth-focality tradeoff of existing TMS coils. The most widely used figure-of-8 coils stimulate brain regions just superficially under the coil, missing deep brain regions known to be critically involved in psychiatric disorders; while ring-type coils can stimulate deep into the brain, but stimulate a large brain volume (lack of focality). A new coil design strategy is proposed: magnetic materials encompassing the human head are optimized to shape the electromagnetic field generated by the primary coil. Specifically, a mathematical model was developed to describe the physical problem; the magnetic materials were discretized into unit blocks; Newtons gradient descent method was applied to iteratively optimize the spatial distribution of the unit blocks to achieve a desired electric field distribution inside a head model. Results reveal that the proposed design achieves a coil penetration depth equal to or better than state-of-the art commercial coils, while improving the depth-focality tradeoff by a factor of 2.2 to 2.7. As a proof-of-concept, a prototype coil and a spherical head model were constructed; the spatial distribution of the induced electric field inside the head model was mapped. Results validated the proposed coil design. TMS coils based on this novel design strategy could potentially lead to better therapeutic outcome.

bioengineering↗

bioRxiv2021

Angle-Tuned Coils: Enabling Building Blocks for High Performance and Multisite TMS Systems

Coordinated whole-brain neural dynamics are essential for proper control of the functionality of different brain systems. Multisite simultaneous or sequential stimulations may provide tools for mechanistic studies of brain functions and the treatment of neuropsychiatric disorders. Conventional circular and figure-8 Transcranial Magnetic Stimulation (TMS) coils occupy a large footprint, and it is difficult to reach desired multiple stimulation locations with close proximity for comprehensive multisite stimulations. These conventional coils, limited by the depth-spread tradeoff rule, also lack the required focality for targeted stimulations. In this work, we propose and demonstrate angle-tuned TMS (AT) coils with an intrinsically reduced footprint with their geometric arrangements of stacking and angle tuning. The stimulation depth can be adjusted with the coil stacking number, and the field spread can be reduced by increasing the tilted wire-wrapping angle of the coils. With either smaller or larger diameter coils than a standard commercial figure-8 coil, we show, theoretically and experimentally, improved field decay rate and field intensity, and the reduced field spread spot size at different stimulation depths. These results indicate that the proposed novel coil establishes a better depth-spread tradeoff curve than the conventional circular and figure-8 coils. This coil design has a simple and single element structure and provides a promising solution for an improved multisite brain stimulation performance and serves as the building block of more complex coils for further depth-spread improvements.

neuroscience↗