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Nielsen, J. D.

Publications and source records attributed to Nielsen, J. D..

3 recordsLinked to original sources

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↗

Evaluating the Influence of Anatomical Accuracy and Electrode Positions on EEG Forward Solutions

Generating realistic volume conductor models for forward calculations in electroencephalography (EEG) is not trivial and several factors contribute to the accuracy of such models, two of which are its anatomical accuracy and the accuracy with which electrode positions are known. Here, we investigate effects of anatomical accuracy by comparing forward solutions from SimNIBS, a tool which allows state-of-the-art anatomical modeling, with well-established pipelines in MNE-Python and FieldTrip. We also compare different ways of specifying electrode locations when digitized positions are not available such as transformation of measured positions from standard space and transformation of a manufacturer layout. Substantial effects of anatomical accuracy were seen throughout the entire brain both in terms of field topography and magnitude with SimNIBS generally being more accurate than the pipelines in MNE-Python and FieldTrip. Topographic and magnitude effects were particularly pronounced for MNE-Python which uses a three-layer boundary element method (BEM) model. We attribute these mainly to differences in skull and cerebrospinal fluid (CSF) modeling. Effects of electrode specification method were evident in occipital and posterior areas when using a transformed manufacturer layout whereas transforming measured positions from standard space generally resulted in smaller errors. We suggest modeling the anatomy of the volume conductor as accurately possible and we hope to facilitate this by making it easy to export simulations from SimNIBS to MNE-Python and FieldTrip for further analysis. Likewise, if digitized electrode positions are not available, a set of measured positions on a standard head template may be preferable to those specified by the manufacturer.

neuroscience↗

SimNIBS 2.1: A Comprehensive Pipeline for Individualized Electric Field Modelling for Transcranial Brain Stimulation

Numerical simulation of the electric fields induced by Non-Invasive Brain Stimulation (NIBS), using realistic anatomical head models has gained interest in recent years for understanding the NIBS effects in individual subjects. Although automated tools for generating the head models and performing the electric field simulations have become available, individualized modelling is still not standard practice in NIBS studies. This is likely partly explained by the lack of robustness and usability of the previously available software tools, and partly by the still developing understanding of the link between physiological effects and electric field distributions in the brain. To facilitate individualized modelling in NIBS, we have introduced the SimNIBS (Simulation of NIBS) software package, providing easy-to-use automated tools for electric field modelling. In this article, we give an overview of the modelling pipeline in SimNIBS 2.1, with step-by-step examples of how to run a simulation. Furthermore, we demonstrate a set of scripts for extracting average electric fields for a group of subjects, and finally demonstrate the accuracy of automated placement of standard electrode montages on the head model. SimNIBS 2.1 is freely available at www.simnibs.org.

bioengineering↗