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.

StimFit-A Data-Driven Algorithm for Automated Deep Brain Stimulation Programming.

BACKGROUND: Finding the optimal deep brain stimulation (DBS) parameters from a multitude of possible combinations by trial and error is time consuming and requires highly trained medical personnel. OBJECTIVE: We developed an automated algorithm to identify optimal stimulation settings in Parkinson's disease (PD) patients treated with subthalamic nucleus (STN) DBS based on imaging-derived metrics. METHODS: Electrode locations and monopolar review data of 612 stimulation settings acquired from 31 PD patients were used to train a predictive model for therapeutic and adverse stimulation effects. Model performance was then evaluated within the training cohort using cross-validation and on an independent cohort of 19 patients. We inverted the model by applying a brute-force approach to determine the optimal stimulation sites in the target region. Finally, an optimization algorithm was established to identify optimal stimulation parameters. Suggested stimulation parameters were compared to the ones applied in clinical practice. RESULTS: Predicted motor outcome correlated with observed outcome (R = 0.57, P < 10-10 ) across patients within the training cohort. In the test cohort, the model explained 28% of the variance in motor outcome differences between settings. The stimulation site for maximum motor improvement was located at the dorsolateral border of the STN. When compared to two empirical settings, model-based suggestions more closely matched the setting with superior motor improvement. CONCLUSION: We developed and validated a data-driven model that can suggest stimulation parameters leading to optimal motor improvement while minimizing the risk of stimulation-induced side effects. This approach might provide guidance for DBS programming in the future. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Forest fire induces short-term shifts in soil food webs with consequences for carbon cycling.

We tested for fire-induced (5-6 years post-fire) changes in the structure and functioning of the soil food web along a 3000-km north-south transect across European Russia, spanning all major forest types in the northern hemisphere outside the tropics. The total biomass of the detrital food web, including microbes and invertebrates, was not affected by fire. However, fire reduced the biomass of microfauna and mites, but had no impact on mesofauna or macrofauna. Fire also reduced rates of carbon (C) mobilisation by soil biota. Our results demonstrate that fire-induced shifts in soil food webs have significant short-term effects on forest soil C cycling, but that these effects vary across forest types and geographic locations.

Environmentally friendly method of RNA isolation.

The diversity of organisms, tissues and cells is so great that, to date, no universal method for RNA extraction from these biological materials exist. The RNA isolation technique with a mix of guanidine thiocyanate, phenol, and chloroform is most widely used. Extraction and purification of RNA methods using selling guanidinium-phenol (TRIzol)-based and silica-based column kits have limitations on toxicity, or RNA isolation, particularly for plants, and scaling. The agents' toxicity is particularly relevant when employing for mass analysis in practice while gaining RNA preparations during the pandemics, epizootics, and epiphytotic. In modern diagnostics of infections at the molecular level, powerful RT-PCR technology is used, which amplifies the detection of RNA pathogens by hundreds of millions of times. We proposed obtaining RNA samples from viruses, bacteria, and plants for the reverse transcription reactions with a subsequent amplification of cDNAs by the polymerase chain reaction using potent and nontoxic chaotropic agent ammonium trichloroacetate. The method works in the analytical and preparative range and can be useful in the case of extraordinary circumstances during mass infections. Potentially this method can be adapted for obtaining RNA samples ready for the RT-isothermal PCR in the field.

OSS-DBS: Open-source simulation platform for deep brain stimulation with a comprehensive automated modeling.

In this study, we propose a new open-source simulation platform that comprises computer-aided design and computer-aided engineering tools for highly automated evaluation of electric field distribution and neural activation during Deep Brain Stimulation (DBS). It will be shown how a Volume Conductor Model (VCM) is constructed and examined using Python-controlled algorithms for generation, discretization and adaptive mesh refinement of the computational domain, as well as for incorporation of heterogeneous and anisotropic properties of the tissue and allocation of neuron models. The utilization of the platform is facilitated by a collection of predefined input setups and quick visualization routines. The accuracy of a VCM, created and optimized by the platform, was estimated by comparison with a commercial software. The results demonstrate no significant deviation between the models in the electric potential distribution. A qualitative estimation of different physics for the VCM shows an agreement with previous computational studies. The proposed computational platform is suitable for an accurate estimation of electric fields during DBS in scientific modeling studies. In future, we intend to acquire SDA and EMA approval. Successful incorporation of open-source software, controlled by in-house developed algorithms, provides a highly automated solution. The platform allows for optimization and uncertainty quantification (UQ) studies, while employment of the open-source software facilitates accessibility and reproducibility of simulations.

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.

Engaging dystonia networks with subthalamic stimulation.

Deep brain stimulation is a viable and efficacious treatment option for dystonia. While the internal pallidum serves as the primary target, more recently, stimulation of the subthalamic nucleus (STN) has been investigated. However, optimal targeting within this structure and its complex surroundings have not been studied in depth. Indeed, multiple historical targets that have been used for surgical treatment of dystonia are directly adjacent to the STN. Further, multiple types of dystonia exist, and outcomes are variable, suggesting that not all types would profit maximally from the exact same target. Therefore, a thorough investigation of the neural substrates underlying effects on dystonia symptoms is warranted. Here, we analyze a multi-center cohort of isolated dystonia patients with subthalamic implantations (N = 58) and relate their stimulation sites to improvement of appendicular and cervical symptoms as well as blepharospasm. Stimulation of the ventral oral posterior nucleus of thalamus and surrounding regions was associated with improvement in cervical dystonia, while stimulation of the dorsolateral STN was associated with improvement in limb dystonia and blepharospasm. This dissociation was also evident for structural connectivity, where the cerebellothalamic, corticospinal and pallidosubthalamic tracts were associated with improvement of cervical dystonia, while hyperdirect and subthalamopallidal pathways were associated with alleviation of limb dystonia and blepharospasm. Importantly, a single well-placed electrode may reach the three optimal target sites. On the level of functional networks, improvement of limb dystonia was correlated with connectivity to the corresponding somatotopic regions in primary motor cortex, while alleviation of cervical dystonia was correlated with connectivity to the recently described 'action-mode' network that involves supplementary motor and premotor cortex. Our findings suggest that different types of dystonia symptoms are modulated via distinct networks. Namely, appendicular dystonia and blepharospasm are improved with modulation of the basal ganglia, and, in particular, the subthalamic circuitry, including projections from the primary motor cortex. In contrast, cervical dystonia was more responsive when engaging the cerebello-thalamo-cortical circuit, including direct stimulation of ventral thalamic nuclei. These findings may inform DBS targeting and image-based programming strategies for patient-specific treatment of dystonia.

Deep brain stimulation of symptom-specific networks in Parkinson's disease.

Deep Brain Stimulation can improve tremor, bradykinesia, rigidity, and axial symptoms in patients with Parkinson's disease. Potentially, improving each symptom may require stimulation of different white matter tracts. Here, we study a large cohort of patients (N = 237 from five centers) to identify tracts associated with improvements in each of the four symptom domains. Tremor improvements were associated with stimulation of tracts connected to primary motor cortex and cerebellum. In contrast, axial symptoms are associated with stimulation of tracts connected to the supplementary motor cortex and brainstem. Bradykinesia and rigidity improvements are associated with the stimulation of tracts connected to the supplementary motor and premotor cortices, respectively. We introduce an algorithm that uses these symptom-response tracts to suggest optimal stimulation parameters for DBS based on individual patient's symptom profiles. Application of the algorithm illustrates that our symptom-tract library may bear potential in personalizing stimulation treatment based on the symptoms that are most burdensome in an individual patient.

Mapping dysfunctional circuits in the frontal cortex using deep brain stimulation.

Frontal circuits play a critical role in motor, cognitive and affective processing, and their dysfunction may result in a variety of brain disorders. However, exactly which frontal domains mediate which (dys)functions remains largely elusive. We studied 534 deep brain stimulation electrodes implanted to treat four different brain disorders. By analyzing which connections were modulated for optimal therapeutic response across these disorders, we segregated the frontal cortex into circuits that had become dysfunctional in each of them. Dysfunctional circuits were topographically arranged from occipital to frontal, ranging from interconnections with sensorimotor cortices in dystonia, the primary motor cortex in Tourette's syndrome, the supplementary motor area in Parkinson's disease, to ventromedial prefrontal and anterior cingulate cortices in obsessive-compulsive disorder. Our findings highlight the integration of deep brain stimulation with brain connectomics as a powerful tool to explore couplings between brain structure and functional impairments in the human brain.

Deep Brain Stimulation for Obsessive-Compulsive Disorder: Optimal Stimulation Sites.

BACKGROUND: Deep brain stimulation (DBS) is a promising treatment option for treatment-refractory obsessive-compulsive disorder (OCD). Several stimulation targets have been used, mostly in and around the anterior limb of the internal capsule and ventral striatum. However, the precise target within this region remains a matter of debate. METHODS: Here, we retrospectively studied a multicenter cohort of 82 patients with OCD who underwent DBS of the ventral capsule/ventral striatum and mapped optimal stimulation sites in this region. RESULTS: DBS sweet-spot mapping performed on a discovery set of 58 patients revealed 2 optimal stimulation sites associated with improvements on the Yale-Brown Obsessive Compulsive Scale, one in the anterior limb of the internal capsule that overlapped with a previously identified OCD-DBS response tract and one in the region of the inferior thalamic peduncle and bed nucleus of the stria terminalis. Critically, the nucleus accumbens proper and anterior commissure were associated with beneficial but suboptimal clinical improvements. Moreover, overlap with the resulting sweet- and sour-spots significantly estimated variance in outcomes in an independent cohort of 22 patients from 2 additional DBS centers. Finally, beyond obsessive-compulsive symptoms, stimulation of the anterior site was associated with optimal outcomes for both depression and anxiety, while the posterior site was only associated with improvements in depression. CONCLUSIONS: Our results suggest how to refine targeting of DBS in OCD and may be helpful in guiding DBS programming in existing patients.

Mapping Dysfunctional Circuits in the Frontal Cortex Using Deep Brain Stimulation.

Frontal circuits play a critical role in motor, cognitive, and affective processing - and their dysfunction may result in a variety of brain disorders. However, exactly which frontal domains mediate which (dys)function remains largely elusive. Here, we study 534 deep brain stimulation electrodes implanted to treat four different brain disorders. By analyzing which connections were modulated for optimal therapeutic response across these disorders, we segregate the frontal cortex into circuits that became dysfunctional in each of them. Dysfunctional circuits were topographically arranged from occipital to rostral, ranging from interconnections with sensorimotor cortices in dystonia, with the primary motor cortex in Tourette's syndrome, the supplementary motor area in Parkinson's disease, to ventromedial prefrontal and anterior cingulate cortices in obsessive-compulsive disorder. Our findings highlight the integration of deep brain stimulation with brain connectomics as a powerful tool to explore couplings between brain structure and functional impairment in the human brain.

Polyclonal antibodies against potato spindle tuber viroid RNA.

Ribonucleic acid (RNA) can act as a hapten in the direct immunization of animals. For antigen synthesis, 65 mg of viroid RNA were obtained by in vitro transcription of the recombinant DNA. We received a reasonable immune response in mice and rabbits with synthesized conjugate viroid RNA-lysozyme. Analyses of polyclonal mouse and rabbit antisera as well as estimates of antibody specificity were performed by dot-Enzyme Linked Immunosorbent Assay (ELISA), sandwich ELISA, and northern immunoblotting. Antiserum obtained showed strong cross-reactions with cellular RNA. The viroid polyclonal antibody cross-reactions with cellular RNAs were depleted via titration antibodies by the plant cellular or commercial yeast RNA. We successfully used antibodies against the viroid RNA-lysozyme antigen to detect the wild-type potato viroid and diagnose potato viroid infection. We presume that intrinsic cross-reactions of RNA antibodies are potentially dangerous after nucleic acid vaccination. Research into the specificity of antibodies against viral RNAs is underway.

Bioinformatics Predicted Linear Epitopes of the Major Coat Protein of the Beet Yellows Virus for Detection of the Virus in the Cell Extract of the Infected Plant.

Beet yellows virus, which belongs to the genus Closterovirus, family Closteroviridae and has a significant negative economic impact, has proven to be challenging to detect and diagnose. To obtain antibodies against BYV, we propose an easier bioinformatics approach than the isolation and purification of the wild virus as an antigen. We used the SWISS-MODEL Workspace (Biozentrum Basel) protein 3D prediction program to discover epitopes of major coat protein p22 lying on the surface of the BYV capsid. Sequences coding these epitopes were cloned into plasmid pQE-40 (Qiagen) in frame with mouse dihydrofolate reductase gene. Fused epitopes were expressed in Escherichia coli and isolated by the Ni-NTA affinity chromatography. Murine antibodies were raised against each epitope and in a combination of both and characterized by dot-ELISA and indirect ELISA. We successively used these antibodies for diagnosis of virus disease in systemically infected Tetragonia tetragonioides. We believe the approach described above can be used for diagnostics of difficult-to-obtain and hazardous-to-health viral infections.

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.

Linking profiles of pathway activation with clinical motor improvements - A retrospective computational study.

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.

Optimal deep brain stimulation sites and networks for stimulation of the fornix in Alzheimer's disease.

Deep brain stimulation (DBS) to the fornix is an investigational treatment for patients with mild Alzheimer's Disease. Outcomes from randomized clinical trials have shown that cognitive function improved in some patients but deteriorated in others. This could be explained by variance in electrode placement leading to differential engagement of neural circuits. To investigate this, we performed a post-hoc analysis on a multi-center cohort of 46 patients with DBS to the fornix (NCT00658125, NCT01608061). Using normative structural and functional connectivity data, we found that stimulation of the circuit of Papez and stria terminalis robustly associated with cognitive improvement (R = 0.53, p < 0.001). On a local level, the optimal stimulation site resided at the direct interface between these structures (R = 0.48, p < 0.001). Finally, modulating specific distributed brain networks related to memory accounted for optimal outcomes (R = 0.48, p < 0.001). Findings were robust to multiple cross-validation designs and may define an optimal network target that could refine DBS surgery and programming.

Numerical Study on Electrode Design for Rodent Deep Brain Stimulation With Implantations Cranial to Targeted Nuclei.

The globus pallidus internus and the subthalamic nucleus are common targets for deep brain stimulation to alleviate symptoms of Parkinson's disease and dystonia. In the rodent models, however, their direct targeting is hindered by the relatively large dimensions of applied electrodes. To reduce the neurological damage, the electrodes are usually implanted cranial to the nuclei, thus exposing the non-targeted brain regions to large electric fields and, in turn, possible undesired stimulation effects. In this numerical study, we analyze the spread of the fields for the conventional electrodes and several modifications. As a result, we present a relatively simple electrode design that allows an efficient focalization of the stimulating field in the inferiorly located nuclei.

Chimeric Virus Made from crTMV RNA and the Coat Protein of Potato Leafroll Virus is Targeted to the Nucleolus and Can Infect Nicotiana benthamiana Mechanically.

A genetically engineered chimeric virus crTMV-CP-PLRV composed of the crucifer-infecting tobacco mosaic virus (crTMV) RNA and the potato leafroll virus (PLRV) coat protein (CP) was obtained by agroinfiltration of Nicotiana benthamiana with the binary vector pCambia-crTMV-CPPLRV. The significant levels of the chimeric virus enabled direct visualization of crTMV-CP-PLRV in the cell and to investigate the mechanism of the pathogenesis. Localization of the crTMV-CP-PLRV in plant cells was examined by immunoblot techniques, as well as light, and transmission electron microscopy. The chimera can transfer between vascular and nonvascular tissues. The chimeric virus inoculum is capable to infect N. benthamiana mechanically. The distinguishing feature of the chimeric virus, the RNA virus with the positive genome, was found to localize in the nucleolus. We also investigated the role of the N-terminal sequence of the PLRV P3 coat protein in the cellular localization of the virus. We believe that the gene of the PLRV CP can be substituted with genes from other challenging-to-study plant pathogens to produce other useful recombinant viruses.

Evaluation of Epistemic Uncertainties for Bipolar Deep Brain Stimulation in Rodent Models.

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.

Chimeric Virus as a Source of the Potato Leafroll Virus Antigen.

Large quantities of potato leafroll virus (PLRV) antigen are difficult to obtain because this virus accumulates in plants at a low titer. To overcome this problem, we constructed a binary vector containing chimeric cDNA, in which the coat protein (CP) gene of the crucifer infecting tobacco mosaic virus (crTMV) was substituted for the coat protein gene of PLRV. The PLRV movement protein (MP) gene, which overlaps completely with the CP gene, was doubly mutated to eliminate priming of the PLRV MP translation from ATG codons with no changes to the amino acid sequence of the CP. The untranslated long intergenic region located upstream of the CP gene was removed from the construct. Transcribed powerful tobamovirus polymerase of the produced vector synthesized PLRV CP gene that was, in turn, translated into the protein. CP PLRV packed RNAs from the helical crTMV in spherical virions. Morphology, size and antigenic specificities of the wild-type and chimeric virus were similar. The yield of isolated chimera was about three orders higher than the yield of native PLRV. The genetic manipulations facilitated the generation of antibodies against the chimeric virus, which recognize the wild-type PLRV.