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      OSS-DBS: Open-source simulation platform for deep brain stimulation with a comprehensive automated modeling

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          In this study, we propose a new open-source simulation platform that comprises computer-aided design and computer-aided engineering tools for highly automated evaluation of electric field distribution and neural activation during Deep Brain Stimulation (DBS). It will be shown how a Volume Conductor Model (VCM) is constructed and examined using Python-controlled algorithms for generation, discretization and adaptive mesh refinement of the computational domain, as well as for incorporation of heterogeneous and anisotropic properties of the tissue and allocation of neuron models. The utilization of the platform is facilitated by a collection of predefined input setups and quick visualization routines. The accuracy of a VCM, created and optimized by the platform, was estimated by comparison with a commercial software. The results demonstrate no significant deviation between the models in the electric potential distribution. A qualitative estimation of different physics for the VCM shows an agreement with previous computational studies. The proposed computational platform is suitable for an accurate estimation of electric fields during DBS in scientific modeling studies. In future, we intend to acquire SDA and EMA approval. Successful incorporation of open-source software, controlled by in-house developed algorithms, provides a highly automated solution. The platform allows for optimization and uncertainty quantification (UQ) studies, while employment of the open-source software facilitates accessibility and reproducibility of simulations.

          Author summary

          Volume conductor models for the computation of the potential and current distribution resulting from deep brain stimulation can help research to gain a deeper understanding of the underlying processes as well as in optimization studies. On the other hand, they are extremely valuable for patient-specific therapy planning while avoiding side effects as far as possible. Despite existing high-quality models, further potential exists to increase their level of realism, precision and reliability and to allow robust optimization. Our approach enables high-precision, patient- or atlas-based results for deep brain stimulation while simultaneously exploiting different measures to achieve high computational efficiency. In the development of the simulation software, we follow the goals of Open Science—in particular the principles of open-source, open data and reproducibility. In two benchmark examples, one on the human brain, the other on the rat brain, we were able to clearly demonstrate the accuracy and efficiency of our simulation results in comparison to a high-resolution simulation using a commercial software. The developed platform provides both the scientific community and clinicians with a precise yet easy-to-use simulation tool for scientific optimization studies and patient-specific therapy planning in context of deep brain stimulation.

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          Most cited references20

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          Lead-DBS: a toolbox for deep brain stimulation electrode localizations and visualizations.

          To determine placement of electrodes after deep brain stimulation (DBS) surgery, a novel toolbox that facilitates both reconstruction of the lead electrode trajectory and the contact placement is introduced. Using the toolbox, electrode placement can be reconstructed and visualized based on the electrode-induced artifacts on post-operative magnetic resonance (MR) or computed tomography (CT) images. Correct electrode placement is essential for efficacious treatment with DBS. Post-operative knowledge about the placement of DBS electrode contacts and trajectories is a promising tool for clinical evaluation of DBS effects and adverse effects. It may help clinicians in identifying the best stimulation contacts based on anatomical target areas and may even shorten test stimulation protocols in the future. Fifty patients that underwent DBS surgery were analyzed in this study. After normalizing the post-operative MR/CT volumes into standard Montreal Neurological Institute (MNI)-stereotactic space, electrode leads (n=104) were detected by a novel algorithm that iteratively thresholds each axial slice and isolates the centroids of the electrode artifacts within the MR/CT-images (MR only n=32, CT only n=10, MR and CT n=8). Two patients received four, the others received two quadripolar DBS leads bilaterally, summing up to a total of 120 lead localizations. In a second reconstruction step, electrode contacts along the lead trajectories were reconstructed by using templates of electrode tips that had been manually created beforehand. Reconstructions that were made by the algorithm were finally compared to manual surveys of contact localizations. The algorithm was able to robustly accomplish lead reconstructions in an automated manner in 98% of electrodes and contact reconstructions in 69% of electrodes. Using additional subsequent manual refinement of the reconstructed contact positions, 118 of 120 electrode lead and contact reconstructions could be localized using the toolbox. Taken together, the toolbox presented here allows for a precise and fast reconstruction of DBS contacts by proposing a semi-automated procedure. Reconstruction results can be directly exported to two- and three-dimensional views that show the relationship between DBS contacts and anatomical target regions. The toolbox is made available to the public in form of an open-source MATLAB repository.
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            Waxholm Space atlas of the Sprague Dawley rat brain.

            Three-dimensional digital brain atlases represent an important new generation of neuroinformatics tools for understanding complex brain anatomy, assigning location to experimental data, and planning of experiments. We have acquired a microscopic resolution isotropic MRI and DTI atlasing template for the Sprague Dawley rat brain with 39 μm isotropic voxels for the MRI volume and 78 μm isotropic voxels for the DTI. Building on this template, we have delineated 76 major anatomical structures in the brain. Delineation criteria are provided for each structure. We have applied a spatial reference system based on internal brain landmarks according to the Waxholm Space standard, previously developed for the mouse brain, and furthermore connected this spatial reference system to the widely used stereotaxic coordinate system by identifying cranial sutures and related stereotaxic landmarks in the template using contrast given by the active staining technique applied to the tissue. With the release of the present atlasing template and anatomical delineations, we provide a new tool for spatial orientation analysis of neuroanatomical location, and planning and guidance of experimental procedures in the rat brain. The use of Waxholm Space and related infrastructures will connect the atlas to interoperable resources and services for multi-level data integration and analysis across reference spaces.
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              Modeling the excitability of mammalian nerve fibers: influence of afterpotentials on the recovery cycle.

              Human nerve fibers exhibit a distinct pattern of threshold fluctuation following a single action potential known as the recovery cycle. We developed geometrically and electrically accurate models of mammalian motor nerve fibers to gain insight into the biophysical mechanisms that underlie the changes in axonal excitability and regulate the recovery cycle. The models developed in this study incorporated a double cable structure, with explicit representation of the nodes of Ranvier, paranodal, and internodal sections of the axon as well as a finite impedance myelin sheath. These models were able to reproduce a wide range of experimental data on the excitation properties of mammalian myelinated nerve fibers. The combination of an accurate representation of the ion channels at the node (based on experimental studies of human, cat, and rat) and matching the geometry of the paranode, internode, and myelin to measured morphology (necessitating the double cable representation) were needed to match the model behavior to the experimental data. Following an action potential, the models generated both depolarizing (DAP) and hyperpolarizing (AHP) afterpotentials. The model results support the hypothesis that both active (persistent Na(+) channel activation) and passive (discharging of the internodal axolemma through the paranodal seal) mechanisms contributed to the DAP, while the AHP was generated solely through active (slow K(+) channel activation) mechanisms. The recovery cycle of the fiber was dependent on the DAP and AHP, as well as the time constant of activation and inactivation of the fast Na(+) conductance. We propose that experimentally documented differences in the action potential shape, strength-duration relationship, and the recovery cycle of motor and sensory nerve fibers can be attributed to kinetic differences in their nodal Na(+) conductances.
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                Author and article information

                Contributors
                Role: InvestigationRole: MethodologyRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – original draft
                Role: MethodologyRole: SupervisionRole: Writing – review & editing
                Role: MethodologyRole: Software
                Role: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: Project administrationRole: ResourcesRole: SupervisionRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS Comput Biol
                PLoS Comput. Biol
                plos
                ploscomp
                PLoS Computational Biology
                Public Library of Science (San Francisco, CA USA )
                1553-734X
                1553-7358
                July 2020
                6 July 2020
                : 16
                : 7
                : e1008023
                Affiliations
                [1 ] Institute of General Electrical Engineering, University of Rostock, Rostock, Germany
                [2 ] Institute of Communications Engineering, University of Rostock, Rostock, Germany
                [3 ] Oscar-Langendorff-Institute of Physiology, Rostock University Medical Center, Rostock, Germany
                [4 ] Interdisciplinary Faculty, University of Rostock, Rostock, Germany
                [5 ] Department Life, Light & Matter, University of Rostock, Rostock, Germany
                Ghent University, BELGIUM
                Author notes

                The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0002-4509-4624
                http://orcid.org/0000-0003-0511-0017
                http://orcid.org/0000-0003-1522-494X
                http://orcid.org/0000-0003-3330-4898
                http://orcid.org/0000-0003-1042-2058
                Article
                PCOMPBIOL-D-20-00599
                10.1371/journal.pcbi.1008023
                7384674
                32628719
                c26664f0-7880-4d57-b4bf-cc5e14f69405
                © 2020 Butenko et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 12 April 2020
                : 6 June 2020
                Page count
                Figures: 9, Tables: 1, Pages: 18
                Funding
                Funded by: Deutsche Forschungsgemeinschaft (DE)
                Award ID: SFB 1270/1 - 299150580
                This work and the authors are funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – SFB 1270/1 - 299150580. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and Health Sciences
                Surgical and Invasive Medical Procedures
                Functional Electrical Stimulation
                Biology and Life Sciences
                Cell Biology
                Cellular Types
                Animal Cells
                Neurons
                Biology and Life Sciences
                Neuroscience
                Cellular Neuroscience
                Neurons
                Physical Sciences
                Physics
                Electricity
                Electric Field
                Biology and Life Sciences
                Anatomy
                Body Fluids
                Cerebrospinal Fluid
                Medicine and Health Sciences
                Anatomy
                Body Fluids
                Cerebrospinal Fluid
                Biology and Life Sciences
                Physiology
                Body Fluids
                Cerebrospinal Fluid
                Biology and Life Sciences
                Anatomy
                Nervous System
                Cerebrospinal Fluid
                Medicine and Health Sciences
                Anatomy
                Nervous System
                Cerebrospinal Fluid
                Physical Sciences
                Materials Science
                Materials
                Conductors
                Biology and Life Sciences
                Cell Biology
                Cellular Types
                Animal Cells
                Neurons
                Nerve Fibers
                Axons
                Biology and Life Sciences
                Neuroscience
                Cellular Neuroscience
                Neurons
                Nerve Fibers
                Axons
                Computer and Information Sciences
                Software Engineering
                Computer Software
                Open Source Software
                Engineering and Technology
                Software Engineering
                Computer Software
                Open Source Software
                Science Policy
                Open Science
                Open Source Software
                Research and Analysis Methods
                Bioassays and Physiological Analysis
                Electrophysiological Techniques
                Brain Electrophysiology
                Deep-Brain Stimulation
                Biology and Life Sciences
                Physiology
                Electrophysiology
                Neurophysiology
                Brain Electrophysiology
                Deep-Brain Stimulation
                Biology and Life Sciences
                Neuroscience
                Neurophysiology
                Brain Electrophysiology
                Deep-Brain Stimulation
                Biology and Life Sciences
                Neuroscience
                Brain Mapping
                Deep-Brain Stimulation
                Custom metadata
                vor-update-to-uncorrected-proof
                2020-07-27
                All files related to the submitted manuscript are available at https://github.com/SFB-ELAINE/OSS-DBS.

                Quantitative & Systems biology
                Quantitative & Systems biology

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