Electrical stimulation of biological samples such as tissues and cell cultures attracts growing attention due to its capability of enhancing cell activity, proliferation, and differentiation. ...Eventually, a profound knowledge of the underlying mechanisms paves the way for innovative therapeutic devices. Capacitive coupling is one option of delivering electric fields to biological samples that has advantages regarding biocompatibility. However, its biological mechanism of interaction is not well understood. Experimental findings could be related to voltage-gated channels, which are triggered by changes of the transmembrane potential. Numerical simulations by the finite element method provide a possibility to estimate the transmembrane potential. Since a full resolution of the cell membrane within a macroscopic model would lead to prohibitively expensive models, we suggest the adaptation of an approximate finite element method. Starting from a basic 2.5D model, the chosen method is validated and applied to realistic experimental situations. To understand the influence of the dielectric properties on the modelling outcome, uncertainty quantification techniques are employed. A frequency-dependent influence of the uncertain dielectric properties of the cell membrane on the modelling outcome is revealed. This may have practical implications for future experimental studies. Our methodology can be easily adapted for computational studies relying on experimental data.
The neurosurgical method of deep brain stimulation (DBS) is used to treat symptoms of movement disorders like Parkinson's disease by implanting stimulation electrodes in deep brain areas. The aim of ...this study was to examine the field distribution in DBS and the role of heterogeneous and anisotropic material properties in the brain areas where stimulation is applied. Finite element models of the human brain were developed comprising tissue heterogeneity and anisotropy. The tissue data were derived from averaged magnetic resonance imaging and diffusion tensor imaging datasets. Unilateral stimulation of the subthalamic nucleus (STN) was computed using an accurate model of an electrode used in clinical treatment of DBS extended with an encapsulation layer around the electrode body. Computations of anisotropic and isotropic brain models, which consider resistive tissue properties for unipolar and bipolar electrode configurations, were carried out. Electrode position was varied within an area around the stimulation center. Results have shown a deviation of 2 % between anisotropic and isotropic field distributions in the vicinity of the STN. The sensitivity of this deviation referring to the electrode position remained small, but increased when the electrode position approached areas of high anisotropy.
Objective
With a growing appreciation for interindividual anatomical variability and patient‐specific brain connectivity, advanced imaging sequences offer the opportunity to directly visualize ...anatomical targets for deep brain stimulation (DBS). The lack of quantitative evidence demonstrating their clinical utility, however, has hindered their broad implementation in clinical practice.
Methods
Using fast gray matter acquisition T1 inversion recovery (FGATIR) sequences, the present study identified a thalamic hypointensity that holds promise as a visual marker in DBS. To validate the clinical utility of the identified hypointensity, we retrospectively analyzed 65 patients (26 female, mean age = 69.1 ± 12.7 years) who underwent DBS in the treatment of essential tremor. We characterized its neuroanatomical substrates and evaluated the hypointensity's ability to predict clinical outcome using stimulation volume modeling and voxelwise mapping. Finally, we determined whether the hypointensity marker could predict symptom improvement on a patient‐specific level.
Results
Anatomical characterization suggested that the identified hypointensity constituted the terminal part of the dentatorubrothalamic tract. Overlap between DBS stimulation volumes and the hypointensity in standard space significantly correlated with tremor improvement (R2 = 0.16, p = 0.017) and distance to hotspots previously reported in the literature (R2 = 0.49, p = 7.9e‐4). In contrast, the amount of variance explained by other anatomical atlas structures was reduced. When accounting for interindividual neuroanatomical variability, the predictive power of the hypointensity increased further (R2 = 0.37, p = 0.002).
Interpretation
Our findings introduce and validate a novel imaging‐based marker attainable from FGATIR sequences that has the potential to personalize and inform targeting and programming in DBS for essential tremor. ANN NEUROL 2022;91:613–628
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.
Bone tissue exhibits piezoelectric properties and thus is capable of transforming mechanical stress into electrical potential. Piezoelectricity has been shown to play a vital role in bone adaptation ...and remodelling processes. Therefore, to better understand the interplay between mechanical and electrical stimulation during these processes, strain-adaptive bone remodelling models without and with considering the piezoelectric effect were simulated using the Python-based open-source software framework. To discretise numerical attributes, the finite element method (FEM) was used for the spatial variables and an explicit Euler scheme for the temporal derivatives. The predicted bone apparent density distributions were qualitatively and quantitatively evaluated against the radiographic scan of a human proximal femur and the bone apparent density calculated using a bone mineral density (BMD) calibration phantom, respectively. Additionally, the effect of the initial bone density on the resulting predicted density distribution was investigated globally and locally. The simulation results showed that the electrically stimulated bone surface enhanced bone deposition and these are in good agreement with previous findings from the literature. Moreover, mechanical stimuli due to daily physical activities could be supported by therapeutic electrical stimulation to reduce bone loss in case of physical impairment or osteoporosis. The bone remodelling algorithm implemented using an open-source software framework facilitates easy accessibility and reproducibility of finite element analysis made.
Objective: Measuring neuronal cell activity using microelectrode arrays reveals a great variety of derived signal shapes within extracellular recordings. However, possible mechanisms responsible for ...this variety have not yet been entirely determined, which might hamper any subsequent analysis of the recorded neuronal data. Methods: To investigate this issue, we propose a computational model based on the finite element method describing the electrical coupling between an electrically active neuron and an extracellular recording electrode in detail. This allows for a systematic study of possible parameters that may play an essential role in defining or altering the shape of the measured electrode potential. Results: Our results indicate that neuronal geometry, neurite structure, as well as the actual pathways of input potentials that evoke action potential generation, have a significant impact on the shape of the resulting extracellular electrode recording and explain most of the known variations of signal shapes. Conclusion: The presented models offer a comprehensive insight into the effect of geometrical and morphological factors on the resulting electrode signal. Significance: Computational modeling complemented with experimental measurements shows much promise to yield meaningful insights into the electrical activity of a neuronal network.
Objective: The aim of this study is to propose an adaptive scheme embedded into an open-source environment for the estimation of the neural activation extent during deep brain stimulation and to ...investigate the feasibility of approximating the neural activation extent by thresholds of the field solution. Methods: Open-source solutions for solving the field equation in volume conductor models of deep brain stimulation and computing the neural activation are embedded into a Python package to estimate the neural activation dependent on the dielectric tissue properties and axon parameters by employing a spatially adaptive scheme. Feasibility of the approximation of the neural activation extent by field thresholds is investigated to further reduce the computational expense. Results: The varying extents of neural activation for different patient-specific dielectric properties were estimated with the adaptive scheme. The results revealed the strong influence of the dielectric properties of the encapsulation layer in the acute and chronic phase after surgery. The computational time required to determine the neural activation extent in each studied model case was substantially reduced. Conclusion: The neural activation extent is altered by patient-specific parameters. Threshold values of the electric potential and electric field norm facilitate a computationally efficient method to estimate the neural activation extent. Significance: The presented adaptive scheme is able to robustly determine neural activation extents and field threshold estimates for varying dielectric tissue properties and axon diameters while substantially reducing the computational expense.
The interaction between a charged metal implant surface and a surrounding body fluid (electrolyte solution) leads to ion redistribution and thus to formation of an electrical double layer (EDL). The ...physical properties of the EDL contribute essentially to the formation of the complex implant-biosystem interface. Study of the EDL began in 1879 by Hermann von Helmholtz and still today remains a scientific challenge. The present mini review is focused on introducing the generalized Stern theory of an EDL, which takes into account the orientational ordering of water molecules. To ascertain the plausibility of the generalized Stern models described, we follow the classical model of Stern and introduce two Langevin models for spatial variation of the relative permittivity for point-like and finite sized ions. We attempt to uncover the subtle interplay between water ordering and finite sized ions and their impact on the electric potential near the charged implant surface. Two complementary effects appear to account for the spatial dependency of the relative permittivity near the charged implant surface — the dipole moment vectors of water molecules are predominantly oriented towards the surface and water molecules are depleted due to the accumulation of counterions. At the end the expressions for relative permittivity in both Langevin models were generalized by also taking into account the cavity and reaction field.
•Two cohorts undergoing deep brain stimulation for treatment of Parkinson’s Disease studied.•Patient-specific pathway activations estimated using advanced biophysical models.•An activation profile ...derived from intrapatient DBS protocols associates with motor improvement.•Outcome associates with activation of pathways from motor-relevant cortical regions and pallidothalamic pathways.
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.
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