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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. [ABSTRACT FROM AUTHOR]

The role of bioelectricity in regulating various physiological processes has attracted increasing scientific interest in implementing exogenous electrical stimulations as a therapeutic approach. In particular, electrical stimuli are used clinically in pre-/post-surgery patient care for the musculoskeletal tissues. The reported potential of electric fields (EF) to regulate bone cell homeostasis and kinetics in vitro has further provoked more studies in this field of research. Various customised apparatuses have been developed, and a range of parameters for the applied EFs have been investigated in vitro with bone cells or mesenchymal stem cells. Additionally, biomaterials with conductive or piezo-electric properties have been designed to complement the enhancing effects of the EF on bone regeneration. Despite much research, there remained a significant gap in knowledge due to the diverse range of EF parameters available. Mathematical models are built to facilitate further understanding and zero in on an effective range of EF parameters in silico . However, the diverse range of EF parameters, experimental conditions, and reported analytical output of different works of literature were reported to possess significant variance, making it challenging to accurately model the field in silico . This review categorises the existing experimental approaches and the parameters used to distinguish the potential variables that apply to mathematical modelling. Furthermore, we will discuss existing modelling approaches and models available in the literature. With this, we will concisely highlight the need to categorise EF parameters, osteogenic differentiation initiators and research output., (Creative Commons Attribution license.)

Deep brain stimulation (DBS) is an established treatment for neurodegenerative movement disorders such as Parkinson's disease that mitigates symptoms by overwriting pathological signals from the central nervous system to the motor system. Nearly all computational models of DBS, directly or indirectly, associate clinical improvements with the extent of fiber activation in the vicinity of the stimulating electrode. However, it is not clear how such activation modulates information transmission. Here, we use the exact cable equation for straight or curved axons and show that DBS segregates the signaling pathways into one of the three communicational modes: complete information blockage, uni-, and bi-directional transmission. Furthermore, all these modes respond to the stimulating pulse in an asynchronous but frequency-locked fashion. Asynchrony depends on the geometry of the axon, its placement and orientation, and the stimulation protocol. At the same time, the electrophysiology of the nerve determines frequency-locking. Such a trimodal response challenges the notion of activation as a binary state and studies that correlate it with the DBS outcome. Importantly, our work suggests that a mechanistic understanding of DBS action relies on distinguishing between these three modes of information transmission.

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.

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.