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.

Addressing Model Uncertainties in Finite Element Simulation of Electrically Stimulated Implants for Critical-Size Mandibular Defects.

OBJECTIVE: Electrical stimulation is known to enhance bone healing. Novel electrostimulating devices are currently being developed for the treatment of critical-size bone defects in the mandible. Previous numerical models of these devices did not account for possible uncertainties in the input data. We present the numerical model of an electrically stimulated minipig mandible, including optimization and uncertainty quantification (UQ) methods that allow us to determine the most influential parameters. METHODS: Uncertainties in the optimized finite element model are quantified using the polynomial chaos method that is implemented in the open-source Python toolbox Uncertainpy. The volumes of understimulated, beneficially stimulated, and overstimulated tissue are considered quantities of interest because they may significantly impact the expected healing success. Further, the current is a substantial quantity, limiting the lifetime of a battery-driven stimulation unit. With sensitivity analyses, the most critical parameters in the numerical model can be identified. Thus, we can learn which parameters are particularly relevant, for example, when conceptualizing the stimulation unit or planning the manufacturing process. RESULTS: The results of this study show that the parameters of the electrode-tissue interface (ETI), as well as the conductivity within the defect volume, have the most significant impact on the model results. CONCLUSIONS: The UQ results suggest that careful characterization of the ETI and the dielectric tissue properties is crucial to reduce these uncertainties. SIGNIFICANCE: The numerical model regarding uncertainties yields important implications for reliable implant design and clinical translation.

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.

Towards an optimised deep brain stimulation using a large-scale computational network and realistic volume conductor model.

Objective. Constructing a theoretical framework to improve deep brain stimulation (DBS) based on the neuronal spatiotemporal patterns of the stimulation-affected areas constitutes a primary target.Approach. We develop a large-scale biophysical network, paired with a realistic volume conductor model, to estimate theoretically efficacious stimulation protocols. Based on previously published anatomically defined structural connectivity, a biophysical basal ganglia-thalamo-cortical neuronal network is constructed using Hodgkin-Huxley dynamics. We define a new biomarker describing the thalamic spatiotemporal activity as a ratio of spiking vs. burst firing. The per cent activation of the different pathways is adapted in the simulation to minimise the differences of the biomarker with respect to its value under healthy conditions.Main results.This neuronal network reproduces spatiotemporal patterns that emerge in Parkinson's disease. Simulations of the fibre per cent activation for the defined biomarker propose desensitisation of pallido-thalamic synaptic efficacy, induced by high-frequency signals, as one possible crucial mechanism for DBS action. Based on this activation, we define both an optimal electrode position and stimulation protocol using pathway activation modelling.Significance. A key advantage of this research is that it combines different approaches, i.e. the spatiotemporal pattern with the electric field and axonal response modelling, to compute the optimal DBS protocol. By correlating the inherent network dynamics with the activation of white matter fibres, we obtain new insights into the DBS therapeutic action.

Discrimination between the effects of pulsed electrical stimulation and electrochemically conditioned medium on human osteoblasts.

BACKGROUND: Electrical stimulation is used for enhanced bone fracture healing. Electrochemical processes occur during the electrical stimulation at the electrodes and influence cellular reactions. Our approach aimed to distinguish between electrochemical and electric field effects on osteoblast-like MG-63 cells. We applied 20 Hz biphasic pulses via platinum electrodes for 2 h. The electrical stimulation of the cell culture medium and subsequent application to cells was compared to directly stimulated cells. The electric field distribution was predicted using a digital twin. RESULTS: Cyclic voltammetry and electrochemical impedance spectroscopy revealed partial electrolysis at the electrodes, which was confirmed by increased concentrations of hydrogen peroxide in the medium. While both direct stimulation and AC-conditioned medium decreased cell adhesion and spreading, only the direct stimulation enhanced the intracellular calcium ions and reactive oxygen species. CONCLUSION: The electrochemical by-product hydrogen peroxide is not the main contributor to the cellular effects of electrical stimulation. However, undesired effects like decreased adhesion are mediated through electrochemical products in stimulated medium. Detailed characterisation and monitoring of the stimulation set up and electrochemical reactions are necessary to find safe electrical stimulation protocols.

Contributions of deep learning to automated numerical modelling of the interaction of electric fields and cartilage tissue based on 3D images.

Electric fields find use in tissue engineering but also in sensor applications besides the broad classical application range. Accurate numerical models of electrical stimulation devices can pave the way for effective therapies in cartilage regeneration. To this end, the dielectric properties of the electrically stimulated tissue have to be known. However, knowledge of the dielectric properties is scarce. Electric field-based methods such as impedance spectroscopy enable determining the dielectric properties of tissue samples. To develop a detailed understanding of the interaction of the employed electric fields and the tissue, fine-grained numerical models based on tissue-specific 3D geometries are considered. A crucial ingredient in this approach is the automated generation of numerical models from biomedical images. In this work, we explore classical and artificial intelligence methods for volumetric image segmentation to generate model geometries. We find that deep learning, in particular the StarDist algorithm, permits fast and automatic model geometry and discretisation generation once a sufficient amount of training data is available. Our results suggest that already a small number of 3D images (23 images) is sufficient to achieve 80% accuracy on the test data. The proposed method enables the creation of high-quality meshes without the need for computer-aided design geometry post-processing. Particularly, the computational time for the geometrical model creation was reduced by half. Uncertainty quantification as well as a direct comparison between the deep learning and the classical approach reveal that the numerical results mainly depend on the cell volume. This result motivates further research into impedance sensors for tissue characterisation. The presented approach can significantly improve the accuracy and computational speed of image-based models of electrical stimulation for tissue engineering applications.

Experimental and numerical methods to ensure comprehensible and replicable alternating current electrical stimulation experiments.

Electrical stimulation has received increasing attention for decades for its application in regenerative medicine. Applications range from bone growth stimulation over cartilage regeneration to deep brain stimulation. Despite all research efforts, translation into clinical use has not yet been achieved in all fields. Recent critical assessments have identified limited documentation and monitoring of preclinical in vitro and in vivo experiments as possible reasons hampering clinical translation. In this work, we present experimental and numerical methods to determine the crucial quantities of electrical stimulation such as the electric field or current density. Knowing the stimulation quantities contributes to comprehending the biological response to electrical stimulation and to finally developing a reliable dose-response curve. To demonstrate the methods, we consider a direct contact electrical stimulation experiment that stands representative for a broad class of stimulation experiments. Electrochemical effects are addressed and methods to integrate them into numerical simulations are evaluated. A focus is laid on affordable lab equipment and reproducible open-source software solutions. Finally, clear guidelines to ensure replicability of electrical stimulation experiments are formulated.

Lead-DBS v3.0: Mapping deep brain stimulation effects to local anatomy and global networks.

Following its introduction in 2014 and with support of a broad international community, the open-source toolbox Lead-DBS has evolved into a comprehensive neuroimaging platform dedicated to localizing, reconstructing, and visualizing electrodes implanted in the human brain, in the context of deep brain stimulation (DBS) and epilepsy monitoring. Expanding clinical indications for DBS, increasing availability of related research tools, and a growing community of clinician-scientist researchers, however, have led to an ongoing need to maintain, update, and standardize the codebase of Lead-DBS. Major development efforts of the platform in recent years have now yielded an end-to-end solution for DBS-based neuroimaging analysis allowing comprehensive image preprocessing, lead localization, stimulation volume modeling, and statistical analysis within a single tool. The aim of the present manuscript is to introduce fundamental additions to the Lead-DBS pipeline including a deformation warpfield editor and novel algorithms for electrode localization. Furthermore, we introduce a total of three comprehensive tools to map DBS effects to local, tract- and brain network-levels. These updates are demonstrated using a single patient example (for subject-level analysis), as well as a retrospective cohort of 51 Parkinson's disease patients who underwent DBS of the subthalamic nucleus (for group-level analysis). Their applicability is further demonstrated by comparing the various methodological choices and the amount of explained variance in clinical outcomes across analysis streams. Finally, based on an increasing need to standardize folder and file naming specifications across research groups in neuroscience, we introduce the brain imaging data structure (BIDS) derivative standard for Lead-DBS. Thus, this multi-institutional collaborative effort represents an important stage in the evolution of a comprehensive, open-source pipeline for DBS imaging and connectomics.

Long-term stimulation with alternating electric fields modulates the differentiation and mineralization of human pre-osteoblasts.

Biophysical stimulation by electric fields can promote bone formation in bone defects of critical size. Even though, long-term effects of alternating electric fields on the differentiation of osteoblasts are not fully understood. Human pre-osteoblasts were stimulated over 31 days to gain more information about these cellular processes. An alternating electric field with 0.7 Vrms and 20 Hz at two distances was applied and viability, mineralization, gene expression, and protein release of differentiation factors were analyzed. The viability was enhanced during the first days of stimulation. A higher electric field resulted in upregulation of typical osteogenic markers like osteoprotegerin, osteopontin, and interleukin-6, but no significant changes in mineralization. Upregulation of the osteogenic markers could be detected with a lower electric field after the first days of stimulation. As a significant increase in the mineralized matrix was identified, an enhanced osteogenesis due to low alternating electric fields can be assumed.

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.

Pulsed Electrical Stimulation Affects Osteoblast Adhesion and Calcium Ion Signaling.

An extensive research field in regenerative medicine is electrical stimulation (ES) and its impact on tissue and cells. The mechanism of action of ES, particularly the role of electrical parameters like intensity, frequency, and duration of the electric field, is not yet fully understood. Human MG-63 osteoblasts were electrically stimulated for 10 min with a commercially available multi-channel system (IonOptix). We generated alternating current (AC) electrical fields with a voltage of 1 or 5 V and frequencies of 7.9 or 20 Hz, respectively. To exclude liquid-mediated effects, we characterized the AC-stimulated culture medium. AC stimulation did not change the medium's pH, temperature, and oxygen content. The H2O2 level was comparable with the unstimulated samples except at 5 V_7.9 Hz, where a significant increase in H2O2 was found within the first 30 min. Pulsed electrical stimulation was beneficial for the process of attachment and initial adhesion of suspended osteoblasts. At the same time, the intracellular Ca2+ level was enhanced and highest for 20 Hz stimulated cells with 1 and 5 V, respectively. In addition, increased Ca2+ mobilization after an additional trigger (ATP) was detected at these parameters. New knowledge was provided on why electrical stimulation contributes to cell activation in bone tissue regeneration.

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.

Numerical study on the effect of capacitively coupled electrical stimulation on biological cells considering model uncertainties.

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.

Personalizing Deep Brain Stimulation Using Advanced Imaging Sequences.

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.

Deep brain stimulation electrode modeling in rats.

Deep Brain Stimulation (DBS) is an efficacious treatment option for an increasing range of brain disorders. To enhance our knowledge about the mechanisms of action of DBS and to probe novel targets, basic research in animal models with DBS is an essential research base. Beyond nonhuman primate, pig, and mouse models, the rat is a widely used animal model for probing DBS effects in basic research. Reconstructing DBS electrode placement after surgery is crucial to associate observed effects with modulating a specific target structure. Post-mortem histology is a commonly used method for reconstructing the electrode location. In humans, however, neuroimaging-based electrode localizations have become established. For this reason, we adapt the open-source software pipeline Lead-DBS for DBS electrode localizations from humans to the rat model. We validate our localization results by inter-rater concordance and a comparison with the conventional histological method. Finally, using the open-source software pipeline OSS-DBS, we demonstrate the subject-specific simulation of the VTA and the activation of axon models aligned to pathways representing neuronal fibers, also known as the pathway activation model. Both activation models yield a characterization of the impact of DBS on the target area. Our results suggest that the proposed neuroimaging-based method can precisely localize DBS electrode placements that are essentially rater-independent and yield results comparable to the histological gold standard. The advantages of neuroimaging-based electrode localizations are the possibility of acquiring them in vivo and combining electrode reconstructions with advanced imaging metrics, such as those obtained from diffusion or functional magnetic resonance imaging (MRI). This paper introduces a freely available open-source pipeline for DBS electrode reconstructions in rats. The presented initial validation results are promising.

Using a Digital Twin of an Electrical Stimulation Device to Monitor and Control the Electrical Stimulation of Cells in vitro.

Electrical stimulation for application in tissue engineering and regenerative medicine has received increasing attention in recent years. A variety of stimulation methods, waveforms and amplitudes have been studied. However, a clear choice of optimal stimulation parameters is still not available and is complicated by ambiguous reporting standards. In order to understand underlying cellular mechanisms affected by the electrical stimulation, the knowledge of the actual prevailing field strength or current density is required. Here, we present a comprehensive digital representation, a digital twin, of a basic electrical stimulation device for the electrical stimulation of cells in vitro. The effect of electrochemical processes at the electrode surface was experimentally characterised and integrated into a numerical model of the electrical stimulation. Uncertainty quantification techniques were used to identify the influence of model uncertainties on relevant observables. Different stimulation protocols were compared and it was assessed if the information contained in the monitored stimulation pulses could be related to the stimulation model. We found that our approach permits to model and simulate the recorded rectangular waveforms such that local electric field strengths become accessible. Moreover, we could predict stimulation voltages and currents reliably. This enabled us to define a controlled stimulation setting and to identify significant temperature changes of the cell culture in the monitored voltage data. Eventually, we give an outlook on how the presented methods can be applied in more complex situations such as the stimulation of hydrogels or tissue in vivo.

Computational Analysis of Bone Remodeling in the Proximal Tibia Under Electrical Stimulation Considering the Piezoelectric Properties.

The piezoelectricity of bone is known to play a crucial role in bone adaptation and remodeling. The application of an external stimulus such as mechanical strain or electric field has the potential to enhance bone formation and implant osseointegration. Therefore, in the present study, the objective is to investigate bone remodeling under electromechanical stimulation as a step towards establishing therapeutic strategies. For the first time, piezoelectric bone remodeling in the human proximal tibia under electro-mechanical loads was analyzed using the finite element method in an open-source framework. The predicted bone density distributions were qualitatively and quantitatively assessed by comparing with the computed tomography (CT) scan and the bone mineral density (BMD) calculated from the CT, respectively. The effect of model parameters such as uniform initial bone density and reference stimulus on the final density distribution was investigated. Results of the parametric study showed that for different values of initial bone density the model predicted similar but not identical final density distribution. It was also shown that higher reference stimulus value yielded lower average bone density at the final time. The present study demonstrates an increase in bone density as a result of electrical stimulation. Thus, to minimize bone loss, for example, due to physical impairment or osteoporosis, mechanical loads during daily physical activities could be partially replaced by therapeutic electrical stimulation.

Ambiguity in the interpretation of the low-frequency dielectric properties of biological tissues.

The frequency-dependent behaviour of the dielectric properties of biological tissues in the frequency range below 1 kHz has been under debate since the past century. Here, we reanalyse the raw data of the main resource of the dielectric properties of biological tissues in impedance representation. Employing a Kramers-Kronig validity test and parameter estimation techniques, we can describe the data by two physical parametric models that correspond to opposing biophysical interpretations: on the one hand the data can be explained only by intrinsic tissue properties, but on the other hand evidence for electrode-specific effects can be found for all tissues under investigation. The first interpretation would justify the continued use of a parametric model comprising four Cole-Cole dispersions, which describe the dielectric properties from extremely low to very high frequencies. As an alternative that is in accordance with the second interpretation, we suggest to omit the slowest of the four dispersions in the model and increase the static conductivity to account for a frequency-independent conductivity below 1 kHz.

Mechanisms of pallidal deep brain stimulation: Alteration of cortico-striatal synaptic communication in a dystonia animal model.

Pallidal deep brain stimulation (DBS) is an important option for patients with severe dystonias, which are thought to arise from a disturbance in striatal control of the globus pallidus internus (GPi). The mechanisms of GPi-DBS are far from understood. Although a disturbance of striatal function is thought to play a key role in dystonia, the effects of DBS on cortico-striatal function are unknown. We hypothesised that DBS, via axonal backfiring, or indirectly via thalamic and cortical coupling, alters striatal function. We tested this hypothesis in the dtsz hamster, an animal model of inherited generalised, paroxysmal dystonia. Hamsters (dystonic and non-dystonic controls) were bilaterally implanted with stimulation electrodes in the GPi. DBS (130 Hz), and sham DBS, were performed in unanaesthetised animals for 3 h. Synaptic cortico-striatal field potentials, as well as miniature excitatory postsynaptic currents (mEPSC) and firing properties of medium spiny striatal neurones were recorded in brain slice preparations obtained immediately after EPN-DBS. The main findings were as follows: a. DBS increased cortico-striatal evoked responses in healthy, but not in dystonic tissue. b. Commensurate with this, DBS increased inhibitory control of these evoked responses in dystonic, and decreased inhibitory control in healthy tissue. c. Further, DBS reduced mEPSC frequency strongly in dystonic, and less prominently in healthy tissue, showing that also a modulation of presynaptic mechanisms is likely involved. d. Cellular properties of medium-spiny neurones remained unchanged. We conclude that DBS leads to dampening of cortico-striatal communication, and restores intrastriatal inhibitory tone.