Subthalamic nucleus but not entopeduncular nucleus deep brain stimulation enhances neurogenesis in the SVZ-olfactory bulb system of Parkinsonian rats.

Introduction: Deep brain stimulation (DBS) is a highly effective treatment option in Parkinson's disease. However, the underlying mechanisms of action, particularly effects on neuronal plasticity, remain enigmatic. Adult neurogenesis in the subventricular zone-olfactory bulb (SVZ-OB) axis and in the dentate gyrus (DG) has been linked to various non-motor symptoms in PD, e.g., memory deficits and olfactory dysfunction. Since DBS affects several of these non-motor symptoms, we analyzed the effects of DBS in the subthalamic nucleus (STN) and the entopeduncular nucleus (EPN) on neurogenesis in 6-hydroxydopamine (6-OHDA)-lesioned hemiparkinsonian rats. Methods: In our study, we applied five weeks of continuous bilateral STN-DBS or EPN-DBS in 6-OHDA-lesioned rats with stable dopaminergic deficits compared to 6-OHDA-lesioned rats with corresponding sham stimulation. We injected two thymidine analogs to quantify newborn neurons early after DBS onset and three weeks later. Immunohistochemistry identified newborn cells co-labeled with NeuN, TH and GABA within the OB and DG. As a putative mechanism, we simulated the electric field distribution depending on the stimulation site to analyze direct electric effects on neural stem cell proliferation. Results: STN-DBS persistently increased the number of newborn dopaminergic and GABAergic neurons in the OB but not in the DG, while EPN-DBS does not impact neurogenesis. These effects do not seem to be mediated via direct electric stimulation of neural stem/progenitor cells within the neurogenic niches. Discussion: Our data support target-specific effects of STN-DBS on adult neurogenesis, a putative modulator of non-motor symptoms in Parkinson's disease.

Understanding the impact of modiolus porosity on stimulation of spiral ganglion neurons by cochlear implants.

Moderate-to-profound sensorineural hearing loss in humans is treatable by electrically stimulating the auditory nerve (AN) with a cochlear implant (CI). In the cochlea, the modiolus presents a porous bony interface between the CI electrode and the AN. New bone growth caused by the presence of the CI electrode or neural degeneration inflicted by ageing or otological diseases might change the effective porosity of the modiolus and, thereby, alter its electrical material properties. Using a volume conductor description of the cochlea, with the aid of a 'mapped conductivity' method and an ad-hoc 'regionally kinetic' equation system, we show that even a slight variation in modiolus porosity or pore distribution can disproportionately affect AN stimulation. Hence, because of porosity changes, an inconsistent CI performance might occur if neural degeneration or new bone growth progress after implantation. Appropriate electrical material properties in accordance with modiolar morphology and pathology should be considered in patient-specific studies. The present first-of-its-kind in-silico study advocates for contextual experimental studies to further explore the utility of modiolus porous morphology in optimising the CI outcome.

Modeling and simulation for prediction of multiple sclerosis progression.

In light of extensive work that has created a wide range of techniques for predicting the course of multiple sclerosis (MS) disease, this paper attempts to provide an overview of these approaches and put forth an alternative way to predict the disease progression. For this purpose, the existing methods for estimating and predicting the course of the disease have been categorized into clinical, radiological, biological, and computational or artificial intelligence-based markers. Weighing the weaknesses and strengths of these prognostic groups is a profound method that is yet in need and works directly at the level of diseased connectivity. Therefore, we propose using the computational models in combination with established connectomes as a predictive tool for MS disease trajectories. The fundamental conduction-based Hodgkin-Huxley model emerged as promising from examining these studies. The advantage of the Hodgkin-Huxley model is that certain properties of connectomes, such as neuronal connection weights, spatial distances, and adjustments of signal transmission rates, can be taken into account. It is precisely these properties that are particularly altered in MS and that have strong implications for processing, transmission, and interactions of neuronal signaling patterns. The Hodgkin-Huxley (HH) equations as a point-neuron model are used for signal propagation inside a small network. The objective is to change the conduction parameter of the neuron model, replicate the changes in myelin properties in MS and observe the dynamics of the signal propagation across the network. The model is initially validated for different lengths, conduction values, and connection weights through three nodal connections. Later, these individual factors are incorporated into a small network and simulated to mimic the condition of MS. The signal propagation pattern is observed after inducing changes in conduction parameters at certain nodes in the network and compared against a control model pattern obtained before the changes are applied to the network. The signal propagation pattern varies as expected by adapting to the input conditions. Similarly, when the model is applied to a connectome, the pattern changes could give an insight into disease progression. This approach has opened up a new path to explore the progression of the disease in MS. The work is in its preliminary state, but with a future vision to apply this method in a connectome, providing a better clinical tool.

Cell-cell interactions and fluctuations in the direction of motility promote directed migration of osteoblasts in direct current electrotaxis.

Under both physiological (development, regeneration) and pathological conditions (cancer metastasis), cells migrate while sensing environmental cues in the form of mechanical, chemical or electrical stimuli. In the case of bone tissue, osteoblast migration is essential in bone regeneration. Although it is known that osteoblasts respond to exogenous electric fields, the underlying mechanism of electrotactic collective movement of human osteoblasts is unclear. Here, we present a computational model that describes the osteoblast cell migration in a direct current electric field as the motion of a collection of active self-propelled particles and takes into account fluctuations in the direction of single-cell migration, finite-range cell-cell interactions, and the interaction of a cell with the external electric field. By comparing this model with in vitro experiments in which human primary osteoblasts are exposed to a direct current electric field of different field strengths, we show that cell-cell interactions and fluctuations in the migration direction promote anode-directed collective migration of osteoblasts.

The interplay of collagen/bioactive glass nanoparticle coatings and electrical stimulation regimes distinctly enhanced osteogenic differentiation of human mesenchymal stem cells.

Increasing research has incorporated bioactive glass nanoparticles (BGN) and electric field (EF) stimulation for bone tissue engineering and regeneration applications. However, their interplay and the effects of different EF stimulation regimes on osteogenic differentiation of human mesenchymal stem cells (hMSC) are less investigated. In this study, we introduced EF with negligible magnetic field strength through a well-characterized transformer-like coupling (TLC) system, and applied EF disrupted (4/4) or consecutive (12/12) regime on type I collagen (Col) coatings with/without BGN over 28 days. Additionally, dexamethasone was excluded to enable an accurate interpretation of BGN and EF in supporting osteogenic differentiation. Here, we demonstrated the influences of BGN and EF on collagen topography and maintaining coating stability. Coupled with the release profile of Si ions from the BGN, cell proliferation and calcium deposition were enhanced in the Col-BGN samples after 28 days. Further, osteogenic differentiation was initiated as early as d 7, and each EF regime was shown to activate distinct pathways. The disrupted (4/4) regime was associated with the BMP/Smad4 pathways that up-regulate Runx2/OCN gene expression on d 7, with a lesser effect on ALP activity. In contrast, the canonical Wnt/ß-Catenin signaling pathway activated through mechanotransduction cues is associated with the consecutive (12/12) regime, with significantly elevated ALP activity and Sp7 gene expression reported on d 7. In summary, our results illustrated the synergistic effects of BGN and EF in different stimulation regimes on osteogenic differentiation that can be further exploited to enhance current bone tissue engineering and regeneration approaches. STATEMENT OF SIGNIFICANCE: The unique release mechanisms of silica from bioactive glass nanoparticles (BGN) were coupled with pulsatile electric field (EF) stimulation to support hMSC osteogenic differentiation, in the absence of dexamethasone. Furthermore, the interplay with consecutive (12/12) and disrupted (4/4) stimulation regimes was investigated. The reported physical, mechanical and topographical effects of BGN and EF on the collagen coating, hMSC and the distinct progression of osteogenic differentiation (canonical Wnt/ß-Catenin and BMP/Smad) triggered by respective stimulation regime were not explicitly reported previously. These results provide the fundamentals for further exploitations on BGN composites with metal ions and rotation of EF regimes to enhance osteogenic differentiation. The goal is sustaining continual osteogenic differentiation and achieving a more physiologically-relevant state and bone constructs in vitro.

Influence of Neuronal Morphology on the Shape of Extracellular Recordings With Microelectrode Arrays: A Finite Element Analysis.

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.

A General Theoretical Framework to Study the Influence of Electrical Fields on Mesenchymal Stem Cells.

Mesenchymal stem cell dynamics involve cell proliferation and cell differentiation into cells of distinct functional type, such as osteoblasts, adipocytes, or chondrocytes. Electrically active implants influence these dynamics for the regeneration of the cells in damaged tissues. How applied electric field influences processes of individual stem cells is a problem mostly unaddressed. The mathematical approaches to study stem cell dynamics have focused on the stem cell population as a whole, without resolving individual cells and intracellular processes. In this paper, we present a theoretical framework to describe the dynamics of a population of stem cells, taking into account the processes of the individual cells. We study the influence of the applied electric field on the cellular processes. We test our mean-field theory with the experiments from the literature, involving in vitro electrical stimulation of stem cells. We show that a simple model can quantitatively describe the experimentally observed time-course behavior of the total number of cells and the total alkaline phosphate activity in a population of mesenchymal stem cells. Our results show that the stem cell differentiation rate is dependent on the applied electrical field, confirming published experimental findings. Moreover, our analysis supports the cell density-dependent proliferation rate. Since the experimental results are averaged over many cells, our theoretical framework presents a robust and sensitive method for determining the effect of applied electric fields at the scale of the individual cell. These results indicate that the electric field stimulation may be effective in promoting bone regeneration by accelerating osteogenic differentiation.

Neural Tissue Degeneration in Rosenthal's Canal and Its Impact on Electrical Stimulation of the Auditory Nerve by Cochlear Implants: An Image-Based Modeling Study.

Sensorineural deafness is caused by the loss of peripheral neural input to the auditory nerve, which may result from peripheral neural degeneration and/or a loss of inner hair cells. Provided spiral ganglion cells and their central processes are patent, cochlear implants can be used to electrically stimulate the auditory nerve to facilitate hearing in the deaf or severely hard-of-hearing. Neural degeneration is a crucial impediment to the functional success of a cochlear implant. The present, first-of-its-kind two-dimensional finite-element model investigates how the depletion of neural tissues might alter the electrically induced transmembrane potential of spiral ganglion neurons. The study suggests that even as little as 10% of neural tissue degeneration could lead to a disproportionate change in the stimulation profile of the auditory nerve. This result implies that apart from encapsulation layer formation around the cochlear implant electrode, tissue degeneration could also be an essential reason for the apparent inconsistencies in the functionality of cochlear implants.

Extracellular Stimulation of Neural Tissues: Activating Function and Sub-threshold Potential Perspective.

Electric stimulation of neural tissues has been an effective clinical intervention to address a variety of pathological issues such as profound deafness, retinal diseases, and Parkinson's disease. However, the knowledge about the exact mechanism of neural excitation, especially activation sites is still ambiguous. Nevertheless, in silico models utilize two approaches namely activating function and sub-threshold potential to predict the activation sites of neural tissues. This paper studies the applicability of these two approaches to model the electric stimulation of pyramidal neuron and spiral ganglion neurons using finite element models. The simulation results suggest that the activating function could be prone to geometrical irregularities of the neural tissues, yet realistically predicts the activation sites on the myelinated neurons. In contrast, the sub-threshold potential predicts the activation of unmyelinated axons by considering the electrophysiological properties of neural tissues. The present study suggests that it is necessary to choose an appropriate method to estimate the neural activation sites while modeling the extracellular stimulation of neural tissues.

3D axonal network coupled to Microelectrode Arrays: A simulation model to study neuronal dynamics.

Action Potentials in a neuron are generated and propagated by exchange of ions through the membrane. The model of Hodgkin and Huxley (HH) describes these time-dependent complex ion dynamics. We have implemented the FitzHugh-Nagumo model, one of the simplified versions of HH model on a pyramidal neuron with branches of axons to study the spontaneous activity of neurons. The network is then coupled to Micro-Electrode Arrays to record the extracellular potential in a neurochip environment. This in silico model is used to study the coupling of AP with the electrodes. Such a model is also a first step to investigate the morphological influence of neurons on their signaling properties.