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Background: Deep brain stimulation (DBS) is an established therapy for patients with Parkinson's disease. In silico computer models for DBS hold the potential to inform a selection of stimulation parameters. In recent years, the focus has shifted towards DBS-induced firing in myelinated axons, deemed particularly relevant for the external modulation of neural activity., Objective: The aim of this project was to investigate correlations between patient-specific pathway activation profiles and clinical motor improvement., Methods: We used the concept of pathway activation modeling, which incorporates advanced volume conductor models and anatomically authentic fiber trajectories to estimate DBS-induced action potential initiation in anatomically plausible pathways that traverse in close proximity to targeted nuclei. We applied the method on two retrospective datasets of DBS patients, whose clinical improvement had been evaluated according to the motor part of the Unified Parkinson's Disease Rating Scale. Based on differences in outcome and activation levels for intrapatient DBS protocols in a training cohort, we derived a pathway activation profile that theoretically induces a complete alleviation of symptoms described by UPDRS-III. The profile was further enhanced by analyzing the importance of matching activation levels for individual pathways., Results: The obtained profile emphasized the importance of activation in pathways descending from the motor-relevant cortical regions as well as the pallidothalamic pathways. The degree of similarity of patient-specific profiles to the optimal profile significantly correlated with clinical motor improvement in a test cohort., Conclusion: Pathway activation modeling has a translational utility in the context of motor symptom alleviation in Parkinson's patients treated with DBS., Competing Interests: Declaration of Competing Interest J.V. have business relationships with Medtronic, Abbott, and Boston Scientific, which are makers of DBS devices, outside the submitted work. A.A.K. reports personal fees and non-financial support from Medtronic, personal fees from Boston Scientific, grants and personal fees from Abbott, outside the submitted work. M.R. reports grant support and honoraria for speaking from Medtronic and Boston Scientific, outside the submitted work. A.H. reports lecture fees for Medtronic and Boston Scientific and is a consultant for AlphaOmega. G.R.W received travel expenses and attendance fees by Boston Scientific and Ipsen Pharma. K.B., N.L., C.N., J.R., H.E. and U.v.R. have nothing to disclose., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Rodent models are widely used in research on deep brain stimulation (DBS) for testing hypotheses of the action mechanism. However, differences in anatomy and technology for DBS in humans and rodents might lead to a non-identical effect on the neural activity. Particularly, strong deviations can be introduced by epistemic uncertainties related to the electrode implantation. In this study, the influence of encapsulation layer properties and implantation precision on axonal activation is quantified using polynomial chaos expansion. In order to improve the efficiency of computations, three truncation methods for the signal frequency spectrum are proposed and evaluated, allowing a tenfold speedup in the particular study. The results of uncertainty quantification on the axonal activity inside the targeted nucleus suggest a major effect of the encapsulation thickness, while the precision of implantation is found to be crucial due to possible direct activation in neighboring structures.

Electrical stimulation is a promising approach to enhance cell viability and differentiation. We aim to develop a stimulation device for the investigation and realization of cartilaginous cell engineering. The stimulation setup is capable of applying well-defined electric fields to several scaffolds at the same time. The setup consists of a flat plate with multiple test tubes for the scaffolds. A flexible printed circuit board containing a separate pair of electrodes for each tube is fixed at the bottom of the plate. In this context, numerical simulation using Finite Element Method (FEM) is a valuable tool to gain a better understanding of the electric field distribution in such devices. The thin insulating layer of the flexible printed circuit board allows sufficient field strength to be achieved at moderate input voltages but presents challenges for modelling. In simulations, thin layers would usually require a fine discretization with many degrees of freedom (DOF). This leads to large models, which are expensive regarding memory and computation time. Based on the 'contact impedance' boundary condition available in COMSOL Multiphysics® 5.4, an alternative approach is proposed that can model thin layers in capacitively coupled setups. The resulting electric field distribution in the new stimulation setup is presented and discussed.

The bio-chemo-mechanical model has many applications in modelling cell contractility. In simulations this model usually is coupled to the continuum mechanics of the cell by defining a large number of directions for stress fibres at each point. In this paper, another representation for coupling the biochemical processes in the bio-chemo-mechanical model is introduced. Using a quadratic form to represent the angular dependency of the activation level, the model's number of degrees of freedom is significantly reduced. Numerical results similar to the original representation are obtained while a significant improvement in computation time is achieved., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Objective: Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation technique to modify neural excitability. Using multi-array tDCS, we investigate the influence of inter-individually varying head tissue conductivity profiles on optimal electrode configurations for an auditory cortex stimulation., Approach: In order to quantify the uncertainty of the optimal electrode configurations, multi-variate generalized polynomial chaos expansions of the model solutions are used based on uncertain conductivity profiles of the compartments skin, skull, gray matter, and white matter. Stochastic measures, probability density functions, and sensitivity of the quantities of interest are investigated for each electrode and the current density at the target with the resulting stimulation protocols visualized on the head surface., Main Results: We demonstrate that the optimized stimulation protocols are only comprised of a few active electrodes, with tolerable deviations in the stimulation amplitude of the anode. However, large deviations in the order of the uncertainty in the conductivity profiles could be noted in the stimulation protocol of the compensating cathodes. Regarding these main stimulation electrodes, the stimulation protocol was most sensitive to uncertainty in skull conductivity. Finally, the probability that the current density amplitude in the auditory cortex target region is supra-threshold was below 50%., Significance: The results suggest that an uncertain conductivity profile in computational models of tDCS can have a substantial influence on the prediction of optimal stimulation protocols for stimulation of the auditory cortex. The investigations carried out in this study present a possibility to predict the probability of providing a therapeutic effect with an optimized electrode system for future auditory clinical and experimental procedures of tDCS applications.