Uncertainty Quantification of Oscillation Suppression During DBS in a Coupled Finite Element and Network Model

Schmidt, Christian; Dunn, Eleanor; Lowery, Madeleine M.; Rienen, Ursula van

doi:10.1109/tnsre.2016.2608925

Cited by 6 publications

(3 citation statements)

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“…To investigate the consequences of the observed changes on the efficacy of neural stimulation, we examined the electrical field distribution and activation of axon collaterals, shown to be preferentially activated during DBS, using computational models [55,56]. For modelling purposed, the electrode has been assumed to be an ideal, partially polarizable electrode, which behaves as a leaky capacitor in line with the stimulation parameters applied within the limits of linearity.…”

Section: Discussionmentioning

confidence: 99%

Stimulation-induced changes at the electrode–tissue interface and their influence on deep brain stimulation

et al. 2022

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Objective: During deep brain stimulation (DBS) the electrode-tissue interface forms a critical path between device and brain tissue. Although changes in the electrical double layer and glial scar can impact stimulation efficacy, the effects of chronic DBS on the electrode-tissue interface have not yet been established. Approach: In this study, we characterised the electrode-tissue interface surrounding chronically implanted DBS electrodes in rats and compared the impedance and histological properties at the electrode interface in animals that received daily stimulation and in those where no stimulation was applied, up to eight weeks post-surgery. A computational model was developed based on the experimental data, which allowed the dispersive electrical properties of the surrounding encapsulation tissue to be estimated. The model was then used to study the effect of stimulation-induced changes in the electrode-tissue interface on the electric field and neural activation during voltage- and current-controlled stimulation. Main results: Incorporating the observed changes in simulations in silico, we estimated the frequency-dependent dielectric properties of the electrical double layer and surrounding encapsulation tissue. Through simulations we show how stimulation-induced changes in the properties of the electrode-tissue interface influence the electric field and alter neural activation during voltage-controlled stimulation. A substantial increase in the number of stimulated collaterals, and their distance from the electrode, was observed during voltage-controlled stimulation with stimulated ETI properties. In vitro examination of stimulated electrodes confirmed that high frequency stimulation leads to desorption of proteins at the electrode interface, with a concomitant reduction in impedance. Significance: The demonstration of stimulation-induced changes in the electrode-tissue interface has important implications for future DBS systems including closed-loop systems where the applied stimulation may change over time. Understanding these changes is particularly important for systems incorporating simultaneous stimulation and sensing, which interact dynamically with brain networks.

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Section: Discussionmentioning

confidence: 99%

Stimulation-induced changes at the electrode–tissue interface and their influence on deep brain stimulation

et al. 2022

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“…second derivative of extracellular potentials along the axon). Nevertheless, these QSA errors are typically smaller than the errors of field amplitude due to uncertainty of tissue conductivity, which can have a wide range of values in the literature with maxto-min ratio between 1.5 to over 10 or 50% and higher deviation compared to the mean [6,82,[89][90][91][92]. Therefore, the selection of the fixed frequency and of the corresponding conductivity can have profound effects on the modeled E-field and predicted activation thresholds due to the sensitivity of the solutions to the conductivity [3,5,6].…”

Section: Frequency Dependence Of Tissue Electric Parameters and Influ...mentioning

confidence: 99%

Quasistatic approximation in neuromodulation

Wang,

Peterchev,

Gaugain

et al. 2024

J. Neural Eng.

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We define and explain the quasistatic approximation (QSA) as applied to field modeling for electrical and magnetic stimulation. Neuromodulation analysis pipelines include discrete stages, and QSA is applied specifically when calculating the electric and magnetic fields generated in tissues by a given stimulation dose. QSA simplifies the modeling equations to support tractable analysis, enhanced understanding, and computational efficiency. The application of QSA in neuro-modulation is based on four underlying assumptions: (A1) no wave propagation or self-induction in tissue, (A2) linear tissue properties, (A3) purely resistive tissue, and (A4) non-dispersive tissue. As a consequence of these assumptions, each tissue is assigned a fixed conductivity, and the simplified equations (e.g., Laplace’s equation) are solved for the spatial distribution of the field, which is separated from the field’s temporal waveform. Recognizing that electrical tissue properties may be more complex, we explain how QSA can be embedded in parallel or iterative pipelines to model frequency dependence or nonlinearity of conductivity. We survey the history and validity of QSA across specific applications, such as microstimulation, deep brain stimulation, spinal cord stimulation, transcranial electrical stimulation, and transcranial magnetic stimulation. The precise definition and explanation of QSA in neuromodulation are essential for rigor when using QSA models or testing their limits.

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“…Our tool can be used for a quick assessment of stimulation PLOS COMPUTATIONAL BIOLOGY protocols or by computational scientists for a complex optimization and UQ analysis. The latter is of a special interest for the DBS community due to uncertainties in brain tissue properties and electrode placement [31][32][33][34]. It is important to emphasize that the platform does not discriminate between targets of DBS or species due to a high parametrization of the algorithms for VCM modeling.…”

Section: Application Of Oss-dbsmentioning

confidence: 99%

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

et al. 2020

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In this study, we propose a new open-source simulation platform that comprises computeraided 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 Pythoncontrolled 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.

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Uncertainty Quantification of Oscillation Suppression During DBS in a Coupled Finite Element and Network Model

Cited by 6 publications

References 50 publications

Stimulation-induced changes at the electrode–tissue interface and their influence on deep brain stimulation

Stimulation-induced changes at the electrode–tissue interface and their influence on deep brain stimulation

Quasistatic approximation in neuromodulation

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

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