Biology subjects

Makarov, S. N.

Publications and source records attributed to Makarov, S. N..

10 recordsLinked to original sources

bioRxiv2022

Genetic or transcranial magnetic stimulation of B-RAF-MEK signaling promotes CST axon sprouting and functional regeneration

Facilitating axon regeneration in the injured central nervous system remains a challenging task. RAF-MEK signaling plays an important role in axon elongation during nervous system development. Here we show that activation of B-RAF in mature corticospinal neurons elicited the expression of a discrete set of transcription factors previously implicated in the regeneration of zebrafish optic nerve axons. Genetic activation of B-RAF-MEK signaling promoted robust regeneration and sprouting of corticospinal tract axons after injury. Newly sprouting axon collaterals formed synaptic connections with spinal interneurons, correlating with the recovery of skilled motor function. Seeking a non-invasive way to stimulate axon regeneration, we found that suprathreshold high-frequency repetitive transcranial magnetic stimulation activates the B-RAF canonical effectors MEK1/2 and requires MEK1/2 activity to promote corticospinal axon regeneration and sprouting after injury. These data demonstrate a central role of neuron-intrinsic RAF-MEK signaling in enhancing the growth capacity of mature corticospinal neurons and propose HF-rTMS as a potential therapy for spinal cord injury. One Sentence SummaryGenetic or HF-rTMS-mediated activation of B-RAF- MEK signaling promotes CST axon sprouting and functional regeneration after a spinal cord injury.

neuroscience↗

bioRxiv2020

A Software Toolkit for TMS Electric-Field Modeling with Boundary Element Fast Multipole Method: An Efficient MATLAB Implementation

BackgroundTranscranial magnetic stimulation (TMS) is currently the only non-invasive neurostimulation modality that enables painless and safe supra-threshold stimulation by employing electromagnetic induction to efficiently penetrate the skull. Accurate, fast, and high resolution modeling of the electric fields (E-fields) may significantly improve individualized targeting and dosing of TMS and therefore enhance the efficiency of existing clinical protocols as well as help establish new application domains. ObjectiveTo present and disseminate our TMS modeling software toolkit, including several new algorithmic developments, and to apply this software to realistic TMS modeling scenarios given a high-resolution model of the human head including cortical geometry and an accurate coil model. MethodThe recently developed charge-based boundary element fast multipole method (BEM-FMM) is employed as an alternative to the 1st order finite element method (FEM) most commonly used today. The BEM-FMM approach provides high accuracy and unconstrained field resolution close to and across cortical interfaces. Here, the previously proposed BEM-FMM algorithm has been improved in several novel ways. Results and ConclusionsThe improvements resulted in a threefold increase in computational speed while maintaining the same solution accuracy. The computational code based on the MATLAB(R) platform is made available to all interested researchers, along with a coil model repository and examples to create custom coils, head model repository, and supporting documentation. The presented software toolkit may be useful for post-hoc analyses of navigated TMS data using high-resolution subject-specific head models as well as accurate and fast modeling for the purposes of TMS coil/hardware development.

bioengineering↗

bioRxiv2020

A Note about the Individualized TMS Focality

A particular yet computationally successful solution of an inverse transcranial magnetic stimulation (TMS) problem is reported. The goal has been focusing the normal unsigned electric field at the inner cortical surface and its vicinity (the D wave activation site) given a unique high-resolution gyral pattern of a subject and a precise coil model. For 16 subjects and 32 arbitrary target points, the solution decreases the mean deviation of the maximum-field domain from the target by a factor of 2 on average. The reduction in the maximum-field area is expected to quadruple. The average final deviation is 6 mm. Rotation about the coil axis is the most significantly altered parameter, and the coil moves 10 mm on average during optimization. The maximum electric field magnitude decreases by 16% on average. Stability of the solution is enforced. The relative average de-focalization is below 1.2 when position/orientation accuracies are within 3 mm/6 degrees, respectively. The solution for the maximum normal field may also maximize the total field and its gradient for neighboring cortical layers III-V (I wave activation).

bioengineering↗

bioRxiv2019

Software Toolkit for Fast High-Resolution TMS Modeling

Computational modeling of Transcranial Magnetic Stimulation (TMS) is a tradeoff between computational speed vs. spatial precision. In this study, we introduce a software toolkit for high-resolution TMS modeling, which may offer the best of both. The toolkit employs the recently developed boundary element fast multipole method (BEM-FMM) with accurate solution computations close to tissue interfaces. It operates within the MATLAB platform and is designed for a broad, medically-oriented computational research community. To enable easy, subject-specific operation, the package is compatible with human head models generated with automated tools such as SimNIBS and FreeSurfer.\n\nBoth coil design in free space as well as efficacy and focality of TMS for a specific subject could be modeled by the package, including optional user-defined parametric loops. Detailed and widely used coil models, generated in both CAD and wire formats, may include several hundred thousand elementary current elements and observation spaces with approximately 1 M field points; the corresponding computational times are on the order of 1 sec. Detailed head models with approximately 1 M triangular facets and a mesh resolution of 0.6 points per mm2 are simulated in approximately 1.5 min which is arguably the fastest time to date. Further reduction of computational times is foreseen. The toolkit is augmented with a population of 16 ready-to-use head models for performing simulations for computational studies that do not involve MRI data collection. The toolkit is also augmented with a coil geometry generator capable of creating accurate coil models.

neuroscience↗

bioRxiv2019

Solving High-Resolution Forward Problems for Extra- and Intracranial Neurophysiological Recordings Using Boundary Element Fast Multipole Method

We present a general numerical approach for solving the forward problem in high-resolution. This approach can be employed in the analysis of noninvasive electroencephalography (EEG) and magnetoencephalography (MEG) as well as invasive electrocorticography (ECoG), stereoencephalography (sEEG), and local field potential (LFP) recordings. The underlying algorithm is our recently developed boundary element fast multipole method (BEM-FMM) that simulates anatomically realistic head models with unprecedented numerical accuracy and speed. This is achieved by utilizing the adjoint double layer formulation and zeroth-order basis functions in conjunction with the FMM acceleration. We present the mathematical formalism in detail and validate the method by applying it to the canonical multilayer sphere problem. The numerical error of BEM-FMM is 2-10 times lower while the computational speed is 1.5-20 times faster than those of the standard first-order FEM. We present four practical case studies: (i) evaluation of the effect of a detailed head model on the accuracy of EEG/MEG forward solution; (ii) demonstration of the ability to accurately calculate the electric potential and the magnetic field in the immediate vicinity of the sources and conductivity boundaries; (iii) computation of the field of a spatially extended cortical equivalent dipole layer; and (iv) taking into account the effect a fontanel for infant EEG source modeling and comparison of the results with a commercially available FEM. In all cases, BEM-FMM provided versatile, fast, and accurate high-resolution modeling of the electromagnetic field and has the potential of becoming a standard tool for modeling both extracranial and intracranial electrophysiological signals.

neuroscience↗

bioRxiv2019

Modeling Primary Fields of TMS Coils with the Fast Multipole Method

AbstractIn this study, an accurate TMS-coil modeling approach based on conductors cross-section representation with many distributed current filaments coupled with an efficient fast multipole method (FMM) accelerator is developed and tested. Uniform (Litz wire) or skin-effect based current distributions are included into consideration. Speed and accuracy estimates as well as two application examples are given, which indicate that this approach is potentially capable of rapid and accurate evaluation of various detailed TMS coil designs and arrays of such coils.\n\nThe MATLAB-based wire and CAD mesh generator for the coil geometry is interfaced with the FMM FORTAN program, which is also compiled within the MATLAB shell. No extra MATLAB toolboxes are necessary. The CAD model of the coil can be imported into any other computational software package in STL format. The algorithm is organized in the form of a MATLAB-based toolkit. First, a coil model is generated using a dedicated script. Then, we compute high-resolution 2D contour plots for any component of the electric and/or magnetic field in coronal, sagittal, and transverse planes via FMM. These two scripts may be further augmented with a parametric loop to enable rapid analysis.\n\nObjectiveWe show how the fast multipole method can be applied to compute primary electric and magnetic fields for detailed TMS coil models

neuroscience↗

bioRxiv2018

Collection of Sixteen High-Quality Human Head CAD Models Generated with SimNIBS 2.1 Using Connectome Subject Data within MATLAB(R) Platform

The goal of this study is to introduce a collection of sixteen high-resolution, 2-manifold CAD compatible head models within the MATLAB platform available to all interested parties for electromagnetic and acoustic simulations. Each model contains skin, skull, CSF, GM, cerebellum, WM, and ventricles head compartments and possesses an \"onion\" topology: the grey matter shell is a container for white matter, ventricles, and cerebellum objects, the CSF shell contains the grey matter shell, the skull shell contains the CSF shell, and finally the skin or scalp shell contains the skull shell. The models are fully compatible with ANSYS ED FEM software, CST Studio Suite, Sim4Life/SEMCAD software, and other electromagnetic software packages.\n\nThe collection is based on MRI data from the Human Connectome Project (HCP) segmented using the SimNIBS 2.1/2.1.1 processing pipeline. The average number of triangular surface facets in a model is 866,000, the average triangle quality is 0.25, the average edge length is 1.48 mm, and the average surface mesh density or resolution is 0.57 points per mm2. If necessary, a finer model mesh can be created for every head using available MATLAB tools.

bioengineering↗

bioRxiv2018

Design and Analysis of a Whole Body Non-Contact Electromagnetic Stimulation Device with Field Modulation

This study describes a whole-body, non-contact electromagnetic stimulation device based on the concept of a conventional MRI Radio Frequency (RF) resonating coil, but at a much lower resonant frequency (100-150 kHz), with a field modulation option (0.5-100 Hz) and with an input power of up to 3 kW. Its unique features include a high electric field level within the biological tissue due to the resonance effect and a low power dissipation level, or a low Specific Absorption Rate (SAR), in the body itself. Because of its large resonator volume together with non-contact coupling, the subject may be located anywhere within the coil over a longer period at moderate and safe electric field levels. The electric field effect does not depend on body position within the resonator. However, field penetration is deep anywhere within the body, including the extremities where muscles, bones, and peripheral tissues are mostly affected. A potential clinical application of this device is treatment of chronic pain. Substantial attention is paid to device safety; this includes both AC power safety and exposure of human subjects to electromagnetic fields. In the former case, we employ inductive coupling which eliminates a direct current path from AC power to the coil. Our design enhances overall device safety at any power level, even when operated under higher-power conditions. Human exposure to electromagnetic fields within the coil is evaluated by performing modeling with two independent numerical methods and with an anatomically realistic multi-tissue human phantom. We show that SAR levels within the body correspond to International Electrotechnical Commission (IEC) safety standards when the input power level of the amplifier driver does not exceed 3 kW. We also show that electric field levels generally comply with International Commission on Non-Ionizing Radiation Protection safety standards if the input power level does not exceed 1.5 kW.

bioengineering↗

bioRxiv2018

Comparative Performance of the Finite Element Method and the Boundary Element Fast Multipole Method for a Test Problem Mimicking Transcranial Magnetic Stimulation (TMS)

A study pertinent to the numerical modeling of cortical neurostimulation is conducted in an effort to compare the performance of the finite element method (FEM) and an original formulation of the boundary element fast multipole method (BEM-FMM) at matched computational performance metrics. We consider two problems: (i) a canonic multi-sphere geometry and an external magnetic-dipole excitation where the analytical solution is available and; (ii) a problem with realistic head models excited by a realistic coil geometry. In the first case, the FEM algorithm tested is a fast open-source getDP solver running within the SimNIBS 2.1.1 environment. In the second case, a high-end commercial FEM software package ANSYS Maxwell 3D is used. The BEM-FMM method runs in the MATLAB(R) 2018a environment.\n\nIn the first case, we observe that the BEM-FMM algorithm gives a smaller solution error for all mesh resolutions and runs significantly faster for high-resolution meshes when the number of triangular facets exceeds approximately 0.25 M. We present other relevant simulation results such as volumetric mesh generation times for the FEM, time necessary to compute the potential integrals for the BEM-FMM, and solution performance metrics for different hardware/operating system combinations. In the second case, we observe an excellent agreement for electric field distribution across different cranium compartments and, at the same time, a speed improvement of three orders of magnitude when the BEM-FMM algorithm used.\n\nThis study may provide a justification for anticipated use of the BEM-FMM algorithm for high-resolution realistic transcranial magnetic stimulation scenarios.

bioengineering↗

bioRxiv2018

Microscopic and Macroscopic Response of a Cortical Neuron to an External Electric Field Computed with the Boundary Element Fast Multipole Method

The goal of this study is to demonstrate how one can compute the activating function and surface charge density resulting from application of an external electric field to a high-resolution realistic neuronal morphology. We use the boundary element fast multipole method (BEM-FMM) on an ordinary computer to accurately perform these computations in under 2-10 minutes for a dense surface mesh of a single neuron with approximately 1.4 million triangles. Prior work used commercial finite element method (FEM) software which required creation of a volumetric tetrahedral mesh between fine neuronal arbor, potentially resulting in prohibitively large volume sizes and long mesh generation times. We used the example of a human pyramidal neuron with an externally applied E-field to show how our approach can quickly and accurately compute the induced surface charge density on the cell surface and the activating function of the cable equation. We found that the induced surface charge density perturbs the macroscopically applied E-field on a microscopic spatial scale. The strength of the perturbation depends on the conductivity contrast; the stronger the contrast, the larger the perturbation. In our example, the induced surface charge density may change the average activating function by up to 75%. We also embedded this neuron model into a detailed macroscopic human head model and simulated a realistic TMS excitation using the BEM-FMM method for the combined model. The solution obtained in this case predicted a smaller activating function error. The difference between the microscopic and the macroscopic effect of the externally applied electric field is of much interest to users of extracellular stimulation techniques and merits further study.

neuroscience↗