A systematic review of studies on anatomical position of electrode contacts used for chronic subthalamic stimulation in Parkinson's disease

Spike-phase coupling of subthalamic neurons to posterior opercular cortex predicts speech sound accuracy

Speech provides a rich context for understanding how cortical interactions with the basal ganglia contribute to unique human behaviors, but opportunities for direct intracranial recordings across cortical-basal ganglia networks are rare. We recorded electrocorticographic signals in the cortex synchronously with single units in the basal ganglia during awake neurosurgeries where subjects spoke syllable repetitions. We discovered that individual STN neurons have transient (200ms) spike-phase coupling (SPC) events with multiple cortical regions. The spike timing of STN neurons was coordinated with the phase of theta-alpha oscillations in the posterior supramarginal and superior temporal gyrus during speech planning and production. Speech sound errors occurred when this STN-cortical interaction was delayed. Our results suggest that the STN supports mechanisms of speech planning and auditory-sensorimotor integration during speech production that are required to achieve high fidelity of the phonological and articulatory representation of the target phoneme. These findings establish a framework for understanding cortical-basal ganglia interaction in other human behaviors, and additionally indicate that firing-rate based models are insufficient for explaining basal ganglia circuit behavior.

The connection of motor improvement after deep brain stimulation in Parkinson's disease and microstructural integrity of the substantia nigra and subthalamic nucleus

BACKGROUND

Nigrostriatal microstructural integrity has been suggested as a biomarker for levodopa response in Parkinson's disease (PD), which is a strong predictor for motor response to deep brain stimulation (DBS) of the subthalamic nucleus (STN). This study aimed to explore the impact of microstructural integrity of the substantia nigra (SN), STN, and putamen on motor response to STN-DBS using diffusion microstructure imaging.

METHODS

Data was collected from 23 PD patients (mean age 63 ± 7, 6 females) who underwent STN-DBS, had preoperative 3 T diffusion magnetic resonance imaging including multishell diffusion-weighted MRI with b-values of 1000 and 2000 s/mm2 and records of motor improvement available.

RESULTS

The association between a poorer DBS-response and increased free interstitial fluid showed notable effect sizes (rho > |0.4|) in SN and STN, but not in putamen. However, this did not reach significance after Bonferroni correction and controlling for sex and age.

CONCLUSION

Microstructural integrity of SN and STN are potential biomarkers for the prediction of therapy efficacy following STN-DBS, but further studies are required to confirm these associations.

Low-frequency stimulation in the zona incerta attenuates seizure via driving GABAergic neuronal activity

BACKGROUND

Managing refractory epilepsy presents a significant a substantial clinical challenge. Deep brain stimulation (DBS) has emerged as a promising avenue for addressing refractory epilepsy. However, the optimal stimulation targets and effective parameters of DBS to reduce seizures remian unidentified.

OBJECTIVES

This study endeavors to scrutinize the therapeutic potential of DBS within the zona incerta (ZI) across diverse seizure models and elucidate the associated underlying mechanisms.

METHODS

We evaluated the therapeutic potential of DBS with different frequencies in the ZI on kainic acid (KA)-induced TLE model or M1-cortical seizures model, pilocarpine-induced M1-cortical seizure models, and KA-induced epilepsy model. Further, employing calcium fiber photometry combined with cell-specific ablation, we sought to clarified the causal role of ZI GABAergic neurons in mediating the therapeutic effects of DBS.

RESULTS

Our findings reveal that DBS in the ZI alleviated the severity of seizure activities in the KA-induced TLE model. Meanwhile, DBS attenuated seizure activities in KA- or pilocarpine-induced M1-cortical seizure model. In addition, DBS exerts a mitigating influence on KA induced epilepsy model. DBS in the ZI showed anti-seizure effects at low frequency spectrum, with 5 Hz exhibiting optimal efficacy. The low-frequency DBS significantly increased the calcium activities of ZI GABAergic neurons. Furthermore, selective ablation of ZI GABAergic neurons with taCasp3 blocked the anti-seizure effect of low-frequency DBS, indicating the anti-seizure effect of DBS is mediated by the activation of ZI GABAergic neurons.

CONCLUSION

Our results demonstrate that low-frequency DBS in the ZI attenuates seizure via driving GABAergic neuronal activity. This suggests that the ZI represents a potential DBS target for treating both hippocampal and cortical seizure through the activation of GABAergic neurons, thereby holding therapeutic significance for seizure treatment.

Long-term follow-up of Parkinsonian patients operated on with deep brain electromodulation without intraoperative microrecording

Background

Deep brain electromodulation (DBEM), also known as deep brain stimulation in different intracerebral targets, is the most widely used surgical treatment due to its effects in reducing motor symptoms of Parkinson's disease. The intracerebral microelectrode recording has been considered for decades as a necessary tool for the success of Parkinson's surgery. However, some publications give more importance to intracerebral stimulation as a better predictive test. Since 2002, we initiated a technique of brain implant of electrodes without micro recording and based solely on image-guided stereotaxis followed by intraoperative macrostimulation. In this work, we analyze our long-term results, taking into account motor skills and quality of life (QL) before and after surgery, and we also establish the patient's time of clinical improvement.

Methods

This is a descriptive clinical study in which the motor state of the patients was evaluated with the unified Parkinson's disease scale (UPDRS) and the QL using the Parkinson's disease QL questionnaire 39 questionnaires before surgery, in the "on" state of the medication; and after surgery, under active stimulation and in the "on" state.

Results

Twenty-four patients with ages ranging from 37 to 78 years undergoing surgery DBEM on the subthalamic nucleus were studied. An improvement of 41.4% in motor skills and 41.7% in QL was obtained.

Conclusion

When microrecording is not available, the results that can be obtained, based on preoperative imaging and clinical intraoperative findings, are optimal and beneficial for patients.

Advances in Deep Brain Stimulation: From Mechanisms to Applications

Deep brain stimulation (DBS) is an effective therapy for various neurologic and neuropsychiatric disorders, involving chronic implantation of electrodes into target brain regions for electrical stimulation delivery. Despite its safety and efficacy, DBS remains an underutilized therapy. Advances in the field of DBS, including in technology, mechanistic understanding, and applications have the potential to expand access and use of DBS, while also improving clinical outcomes. Developments in DBS technology, such as MRI compatibility and bidirectional DBS systems capable of sensing neural activity while providing therapeutic stimulation, have enabled advances in our understanding of DBS mechanisms and its application. In this review, we summarize recent work exploring DBS modulation of target networks. We also cover current work focusing on improved programming and the development of novel stimulation paradigms that go beyond current standards of DBS, many of which are enabled by sensing-enabled DBS systems and have the potential to expand access to DBS.

Long-Term Follow-Up of Unilateral Deep Brain Stimulation Targeting the Caudal Zona Incerta in 13 Patients with Parkinsonian Tremor

INTRODUCTION

Deep brain stimulation (DBS) is an established treatment for Parkinson's disease (PD) and other movement disorders. The ventral intermediate nucleus of the thalamus is considered as the target of choice for tremor disorders, including tremor-dominant PD not suitable for DBS in the subthalamic nucleus (STN). In the last decade, several studies have shown promising results on tremor from DBS in the posterior subthalamic area (PSA), including the caudal zona incerta (cZi) located posteromedial to the STN. The aim of this study was to evaluate the long-term effect of unilateral cZi/PSA-DBS in patients with tremor-dominant PD.

METHODS

Thirteen patients with PD with medically refractory tremor were included. The patients were evaluated using the motor part of the Unified Parkinson Disease Rating Scale (UPDRS) off/on medication before surgery and off/on medication and stimulation 1-2 years (short-term) after surgery and at a minimum of 3 years after surgery (long-term).

RESULTS

At short-term follow-up, DBS improved contralateral tremor by 88% in the off-medication state. This improvement persisted after a mean of 62 months. Contralateral bradykinesia was improved by 40% at short-term and 20% at long-term follow-up, and the total UPDRS-III by 33% at short-term and by 22% at long-term follow-up with stimulation alone.

CONCLUSIONS

Unilateral cZi/PSA-DBS seems to remain an effective treatment for patients with severe Parkinsonian tremor several years after surgery. There was also a modest improvement on bradykinesia.

Anatomical targeting for electrode localization in subthalamic nucleus deep brain stimulation: A comparative study

BACKGROUND AND PURPOSE

In deep brain stimulation (DBS), accurate electrode placement is essential for optimizing patient outcomes. Localizing electrodes enables insight into therapeutic outcomes and development of metrics for use in clinical trials. Methods of defining anatomical targets have been described with varying accuracy and objectivity. To assess variability in anatomical targeting, we compare four methods of defining an appropriate target for DBS of the subthalamic nucleus for Parkinson's disease.

METHODS

The methods compared are direct visualization, red nucleus-based indirect targeting, mid-commissural point-based indirect targeting, and automated template-based targeting. This study assessed 226 hemispheres in 113 DBS recipients (39 females, 73 males, 62.2 ± 7.7 years). We utilized the electrode placement error (the Euclidean distance between the defined target and closest DBS electrode) as a metric for comparative analysis. Pairwise differences in electrode placement error across the four methods were compared using the Kruskal-Wallis H-test and Wilcoxon signed-rank tests.

RESULTS

Interquartile ranges of the differences in electrode placement error spanned 1.18-1.56 mm. A Kruskal-Wallis H-test reported a statistically significant difference in the median of at least two groups (H(5) = 41.052, p < .001). Wilcoxon signed-rank tests reported statistically significant difference in two comparisons: direct visualization versus red nucleus-based indirect, and direct visualization versus automated template-based methods (T < 9215, p < .001).

CONCLUSIONS

All methods were similarly discordant in their relative accuracy, despite having significant technical differences in their application. The differing protocols and technical aspects of each method, however, have the implication that one may be more practical depending on the clinical or research application at hand.

Connectivity Profile for Subthalamic Nucleus Deep Brain Stimulation in Early Stage Parkinson Disease

OBJECTIVE

This study was undertaken to describe relationships between electrode localization and motor outcomes from the subthalamic nucleus (STN) deep brain stimulation (DBS) in early stage Parkinson disease (PD) pilot clinical trial.

METHODS

To determine anatomical and network correlates associated with motor outcomes for subjects randomized to early DBS (n = 14), voxelwise sweet spot mapping and structural connectivity analyses were carried out using outcomes of motor progression (Unified Parkinson Disease Rating Scale Part III [UPDRS-III] 7-day OFF scores [∆baseline➔24 months, MedOFF/StimOFF]) and symptomatic motor improvement (UPDRS-III ON scores [%∆baseline➔24 months, MedON/StimON]).

RESULTS

Sweet spot mapping revealed a location associated with slower motor progression in the dorsolateral STN (anterior/posterior commissure coordinates: 11.07 ± 0.82mm lateral, 1.83 ± 0.61mm posterior, 3.53 ± 0.38mm inferior to the midcommissural point; Montreal Neurological Institute coordinates: +11.25, -13.56, -7.44mm). Modulating fiber tracts from supplementary motor area (SMA) and primary motor cortex (M1) to the STN correlated with slower motor progression across STN DBS subjects, whereas fiber tracts originating from pre-SMA and cerebellum were negatively associated with motor progression. Robustness of the fiber tract model was demonstrated in leave-one-patient-out (R = 0.56, p = 0.02), 5-fold (R = 0.50, p = 0.03), and 10-fold (R = 0.53, p = 0.03) cross-validation paradigms. The sweet spot and fiber tracts associated with motor progression revealed strong similarities to symptomatic motor improvement sweet spot and connectivity in this early stage PD cohort.

INTERPRETATION

These results suggest that stimulating the dorsolateral region of the STN receiving input from M1 and SMA (but not pre-SMA) is associated with slower motor progression across subjects receiving STN DBS in early stage PD. This finding is hypothesis-generating and must be prospectively tested in a larger study. ANN NEUROL 2023;94:271-284.

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.

Towards biomarker-based optimization of deep brain stimulation in Parkinson's disease patients

Background

Subthalamic deep brain stimulation (DBS) is an established therapy to treat Parkinson's disease (PD). To maximize therapeutic outcome, optimal DBS settings must be carefully selected for each patient. Unfortunately, this is not always achieved because of: (1) increased technological complexity of DBS devices, (2) time restraints, or lack of expertise, and (3) delayed therapeutic response of some symptoms. Biomarkers to accurately predict the most effective stimulation settings for each patient could streamline this process and improve DBS outcomes.

Objective

To investigate the use of evoked potentials (EPs) to predict clinical outcomes in PD patients with DBS.

Methods

In ten patients (12 hemispheres), a monopolar review was performed by systematically stimulating on each DBS contact and measuring the therapeutic window. Standard imaging data were collected. EEG-based EPs were then recorded in response to stimulation at 10 Hz for 50 s on each DBS-contact. Linear mixed models were used to assess how well both EPs and image-derived information predicted the clinical data.

Results

Evoked potential peaks at 3 ms (P3) and at 10 ms (P10) were observed in nine and eleven hemispheres, respectively. Clinical data were well predicted using either P3 or P10. A separate model showed that the image-derived information also predicted clinical data with similar accuracy. Combining both EPs and image-derived information in one model yielded the highest predictive value.

Conclusion

Evoked potentials can accurately predict clinical DBS responses. Combining EPs with imaging data further improves this prediction. Future refinement of this approach may streamline DBS programming, thereby improving therapeutic outcomes.

Clinical trial registration

ClinicalTrials.gov, identifier NCT04658641.

Lead location as a determinant of motor benefit in subthalamic nucleus deep brain stimulation for Parkinson’s disease

Background

Subthalamic nucleus (STN) deep brain stimulation (DBS) is regarded as an effective treatment for patients with advanced Parkinson’s disease (PD). Clinical benefit, however, varies significantly across patients. Lead location has been hypothesized to play a critical role in determining motor outcome and may account for much of the observed variability reported among patients.

Objective

To retrospectively evaluate the relationship of lead location to motor outcomes in patients who had been implanted previously at another center by employing a novel visualization technology that more precisely determines the location of the DBS lead and its contacts with respect to each patient’s individually defined STN.

Methods

Anatomical models were generated using novel imaging in 40 PD patients who had undergone bilateral STN DBS (80 electrodes) at another center. Patient-specific models of each STN were evaluated to determine DBS electrode contact locations with respect to anterior to posterior and medial to lateral regions of the individualized STNs and compared to the change in the contralateral hemi-body Unified Parkinson’s Disease Rating Scale Part III (UPDRS-III) motor score.

Results

The greatest improvement in hemi-body motor function was found when active contacts were located within the posterolateral portion of the STN (71.5%). Motor benefit was 52 and 36% for central and anterior segments, respectively. Active contacts within the posterolateral portion also demonstrated the greatest reduction in levodopa dosage (77%).

Conclusion

The degree of motor benefit was dependent on the location of the stimulating contact within the STN. Although other factors may play a role, we provide further evidence in support of the hypothesis that lead location is a critical factor in determining clinical outcomes in STN DBS.

Interrater reliability of deep brain stimulation electrode localizations

Lead-DBS is an open-source, semi-automatized and widely applied software tool facilitating precise localization of deep brain stimulation electrodes both in native as well as in standardized stereotactic space. While automatized preprocessing steps within the toolbox have been tested and validated in previous studies, the interrater reliability in manual refinements of electrode localizations using the tool has not been objectified so far. Here, we investigate the variance introduced in this processing step by different raters when localizing electrodes based on postoperative CT or MRI. Furthermore, we compare the performance of novel trainees that received a structured training and more experienced raters with an expert user. We show that all users yield similar results with an average difference in localizations ranging between 0.52-0.75 mm with 0.07-0.12 mm increases in variability when using postoperative MRI and following normalization to standard space. Our findings may pave the way toward formal training for using Lead-DBS and demonstrate its reliability and ease-of-use for imaging research in the field of deep brain stimulation.

Electrocorticography is superior to subthalamic local field potentials for movement decoding in Parkinson's disease

Brain signal decoding promises significant advances in the development of clinical brain computer interfaces (BCI). In Parkinson's disease (PD), first bidirectional BCI implants for adaptive deep brain stimulation (DBS) are now available. Brain signal decoding can extend the clinical utility of adaptive DBS but the impact of neural source, computational methods and PD pathophysiology on decoding performance are unknown. This represents an unmet need for the development of future neurotechnology. To address this, we developed an invasive brain-signal decoding approach based on intraoperative sensorimotor electrocorticography (ECoG) and subthalamic LFP to predict grip-force, a representative movement decoding application, in 11 PD patients undergoing DBS. We demonstrate that ECoG is superior to subthalamic LFP for accurate grip-force decoding. Gradient boosted decision trees (XGBOOST) outperformed other model architectures. ECoG based decoding performance negatively correlated with motor impairment, which could be attributed to subthalamic beta bursts in the motor preparation and movement period. This highlights the impact of PD pathophysiology on the neural capacity to encode movement vigor. Finally, we developed a connectomic analysis that could predict grip-force decoding performance of individual ECoG channels across patients by using their connectomic fingerprints. Our study provides a neurophysiological and computational framework for invasive brain signal decoding to aid the development of an individualized precision-medicine approach to intelligent adaptive DBS.

Lead-OR: a multimodal platform for deep brain stimulation surgery

Background:

Deep brain stimulation (DBS) electrode implant trajectories are stereotactically defined using preoperative neuroimaging. To validate the correct trajectory, microelectrode recordings (MERs) or local field potential recordings can be used to extend neuroanatomical information (defined by MRI) with neurophysiological activity patterns recorded from micro- and macroelectrodes probing the surgical target site. Currently, these two sources of information (imaging vs. electrophysiology) are analyzed separately, while means to fuse both data streams have not been introduced.

Methods:

Here, we present a tool that integrates resources from stereotactic planning, neuroimaging, MER, and high-resolution atlas data to create a real-time visualization of the implant trajectory. We validate the tool based on a retrospective cohort of DBS patients (N = 52) offline and present single-use cases of the real-time platform.

Results:

We establish an open-source software tool for multimodal data visualization and analysis during DBS surgery. We show a general correspondence between features derived from neuroimaging and electrophysiological recordings and present examples that demonstrate the functionality of the tool.

Conclusions:

This novel software platform for multimodal data visualization and analysis bears translational potential to improve accuracy of DBS surgery. The toolbox is made openly available and is extendable to integrate with additional software packages.

Funding:

Deutsche Forschungsgesellschaft (410169619, 424778381), Deutsches Zentrum für Luft- und Raumfahrt (DynaSti), National Institutes of Health (2R01 MH113929), and Foundation for OCD Research (FFOR).

Deep brain stimulation is an established therapy for patients with Parkinson’s disease and an emerging option for other neurological conditions. Electrodes are implanted deep in the brain to stimulate precise brain regions and control abnormal brain activity in those areas. The most common target for Parkinson’s disease, for instance, is a structure called the subthalamic nucleus, which sits at the base of the brain, just above the brain stem.

To ensure electrodes are placed correctly, surgeons use various sources of information to characterize the patient’s brain anatomy and decide on an implant site. These data include brain scans taken before surgery and recordings of brain activity taken during surgery to confirm the intended implant site. Sometimes, the brain activity signals from this last confirmation step may slightly alter surgical plans. It represents one of many challenges for clinical teams: to analyse, assimilate, and communicate data as it is collected during the procedure.

Oxenford et al. developed a software pipeline to aggregate the data surgeons use to implant electrodes. The open-source platform, dubbed Lead-OR, visualises imaging data and brain activity recordings (termed electrophysiology data) in real time. The current set-up integrates with commercial tools and existing software for surgical planning.

Oxenford et al. tested Lead-OR on data gathered retrospectively from 32 patients with Parkinson’s who had electrodes implanted in their subthalamic nucleus. The platform showed good agreement between imaging and electrophysiology data, although there were some unavoidable discrepancies, arising from limitations in the imaging pipeline and from the surgical procedure. Lead-OR was also able to correct for brain shift, which is where the brain moves ever so slightly in the skull.

With further validation, this proof-of-concept software could serve as a useful decision-making tool for surgical teams implanting electrodes for deep brain stimulation. In time, if implemented, its use could improve the accuracy of electrode placement, translating into better surgical outcomes for patients. It also has the potential to integrate forthcoming ultra-high-resolution data from current brain mapping projects, and other commercial surgical planning tools.

Functional connectivity maps of theta/alpha and beta coherence within the subthalamic nucleus region

The subthalamic nucleus (STN) is a primary target for deep brain stimulation in Parkinson's disease (PD). Although small in size, the STN is commonly partitioned into sensorimotor, cognitive/associative, and limbic subregions based on its structural connectivity profile to cortical areas. We investigated whether such a regional specialization is also supported by functional connectivity between local field potential recordings and simultaneous magnetoencephalography. Using a novel data set of 21 PD patients, we replicated previously reported cortico-STN coherence networks in the theta/alpha and beta frequency ranges, and looked for the spatial distribution of these networks within the STN region. Although theta/alpha and beta coherence peaks were both observed in on-medication recordings from electrode contacts at several locations within and around the STN, sites with theta/alpha coherence peaks were situated at significantly more inferior MNI coordinates than beta coherence peaks. Sites with only theta/alpha coherence peaks, i.e. without distinct beta coherence, were mostly located near the border of sensorimotor and cognitive/associative subregions as defined by a tractography-based atlas of the STN. Peak coherence values were largely unaltered by the medication state of the subject, however, theta/alpha peaks were more often identified in recordings obtained after administration of dopaminergic medication. Our findings suggest the existence of a frequency-specific topography of cortico-STN coherence within the STN, albeit with considerable spatial overlap between functional networks. Consequently, optimization of deep brain stimulation targeting might remain a trade-off between alleviating motor symptoms and avoiding adverse neuropsychiatric side effects.

Neuronal oscillations predict deep brain stimulation outcome in Parkinson's disease

BACKGROUND

Neuronal oscillations are linked to symptoms of Parkinson's disease. This relation can be exploited for optimizing deep brain stimulation (DBS), e.g. by informing a device or human about the optimal location, time and intensity of stimulation. Whether oscillations predict individual DBS outcome is not clear so far.

OBJECTIVE

To predict motor symptom improvement from subthalamic power and subthalamo-cortical coherence.

METHODS

We applied machine learning techniques to simultaneously recorded magnetoencephalography and local field potential data from 36 patients with Parkinson's disease. Gradient-boosted tree learning was applied in combination with feature importance analysis to generate and understand out-of-sample predictions.

RESULTS

A few features sufficed for making accurate predictions. A model operating on five coherence features, for example, achieved correlations of r > 0.8 between actual and predicted outcomes. Coherence comprised more information in less features than subthalamic power, although in general their information content was comparable. Both signals predicted akinesia/rigidity reduction best. The most important local feature was subthalamic high-beta power (20-35 Hz). The most important connectivity features were subthalamo-parietal coherence in the very high frequency band (>200 Hz) and subthalamo-parietal coherence in low-gamma band (36-60 Hz). Successful prediction was not due to the model inferring distance to target or symptom severity from neuronal oscillations.

CONCLUSION

This study demonstrates for the first time that neuronal oscillations are predictive of DBS outcome. Coherence between subthalamic and parietal oscillations are particularly informative. These results highlight the clinical relevance of inter-areal synchrony in basal ganglia-cortex loops and might facilitate further improvements of DBS in the future.

Clinically-derived oscillatory biomarker predicts optimal subthalamic stimulation for Parkinson's disease

OBJECTIVE

Choosing the optimal electrode trajectory, stimulation location, and stimulation amplitude in subthalamic nucleus deep brain stimulation (STN DBS) for Parkinson's disease (PD) remains a time-consuming empirical effort. In this retrospective study, we derive a data-driven electrophysiological biomarker that predicts clinical DBS location and parameters, and we consolidate this information into a quantitative score that may facilitate an objective approach to STN DBS surgery and programming.

APPROACH

Random-forest feature selection was applied to a dataset of 1046 microelectrode recordings sites across 20 DBS implant trajectories to identify features of oscillatory activity that predict clinically programmed volumes of tissue activation (VTA). A cross-validated classifier was used to retrospectively predict VTA regions from these features. Spatial convolution of probabilistic classifier outputs along MER trajectories produced a biomarker score that reflects the probability of localization within a clinically optimized VTA.

MAIN RESULTS

Biomarker scores peaked within the VTA region and were significantly correlated with percent improvement in postoperative motor symptoms (MDS-UPRDS Part III, R = 0.61, p = 0.004). Notably, the length of STN, a common criterion for trajectory selection, did not show similar correlation (R = -0.31, p = 0.18). These findings suggest that biomarker-based trajectory selection and programming may improve motor outcomes by 9 ± 3 percentage points (p = 0.047) in this dataset.

SIGNIFICANCE

A clinically defined electrophysiological biomarker not only predicts VTA size and location but also correlates well with motor outcomes. Use of this biomarker for trajectory selection and initial stimulation may potentially simplify STN DBS surgery and programming.

Neural circuit control of innate behaviors

All animals possess a plethora of innate behaviors that do not require extensive learning and are fundamental for their survival and propagation. With the advent of newly-developed techniques such as viral tracing and optogenetic and chemogenetic tools, recent studies are gradually unraveling neural circuits underlying different innate behaviors. Here, we summarize current development in our understanding of the neural circuits controlling predation, feeding, male-typical mating, and urination, highlighting the role of genetically defined neurons and their connections in sensory triggering, sensory to motor/motivation transformation, motor/motivation encoding during these different behaviors. Along the way, we discuss possible mechanisms underlying binge-eating disorder and the pro-social effects of the neuropeptide oxytocin, elucidating the clinical relevance of studying neural circuits underlying essential innate functions. Finally, we discuss some exciting brain structures recurrently appearing in the regulation of different behaviors, which suggests both divergence and convergence in the neural encoding of specific innate behaviors. Going forward, we emphasize the importance of multi-angle and cross-species dissections in delineating neural circuits that control innate behaviors.

The Contribution of Subthalamic Nucleus Deep Brain Stimulation to the Improvement in Motor Functions and Quality of Life

BACKGROUND

Subthalamic nucleus deep brain stimulation (STN-DBS) effectively treats motor symptoms and quality of life (QoL) of advanced and fluctuating early Parkinson's disease. Little is known about the relation between electrode position and changes in symptom control and ultimately QoL.

OBJECTIVES

The relation between the stimulated part of the STN and clinical outcomes, including the motor score of the Unified Parkinson's Disease Rating Scale (UPDRS) and the quality-of-life questionnaire, was assessed in a subcohort of the EARLYSTIM study.

METHODS

Sixty-nine patients from the EARLYSTIM cohort who underwent DBS, with a comprehensive clinical characterization before and 24 months after surgery, were included. Intercorrelations of clinical outcome changes, correlation between the affected functional parts of the STN, and changes in clinical outcomes were investigated. We further calculated sweet spots for different clinical parameters.

RESULTS

Improvements in the UPDRS III and Parkinson's Disease Questionnaire (PDQ-39) correlated positively with the extent of the overlap with the sensorimotor STN. The sweet spots for the UPDRS III (x = 11.6, y = -13.1, z = -6.3) and the PDQ-39 differed (x = 14.8, y = -12.4, z = -4.3) ~3.8 mm.

CONCLUSIONS

The main influence of DBS on QoL is likely mediated through the sensory-motor basal ganglia loop. The PDQ sweet spot is located in a posteroventral spatial location in the STN territory. For aspects of QoL, however, there was also evidence of improvement through stimulation of the other STN subnuclei. More research is necessary to customize the DBS target to individual symptoms of each patient. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

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.

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.

Surgical Strategy for Directional Deep Brain Stimulation

Deep brain stimulation (DBS) is a well-established treatment for drug-resistant involuntary movements. However, the conventional quadripole cylindrical lead creates electrical fields in all directions, and the resulting spread to adjacent eloquent structures may induce unintended effects. Novel directional leads have therefore been designed to allow directional stimulation (DS). Directional leads have the advantage of widening the therapeutic window (TW), compensating for slight misplacement of the lead and requiring less electrical power to provide the same effect as a cylindrical lead. Conversely, the increase in the number of contacts from four to eight and the addition of directional elements has made stimulation programming more complex. For these reasons, new treatment strategies are required to allow effective directional DBS. During lead implantation, the directional segment should be placed in a "sweet spot," and the orientation of the directional segment is important for programming. Trial-and-error testing of a large number of contacts is unnecessary, and efficient and systematic execution of the programmed procedure is desirable. Recent improvements in imaging technologies have enabled image-guided programming. In the future, optimal stimulations are expected to be programmed by directional recording of local field potentials.

Deep Brain Stimulation of Caudal Zona Incerta for Parkinson's Disease: One-Year Follow-Up and Electric Field Simulations

OBJECTIVE

To evaluate the effects of bilateral caudal zona incerta (cZi) deep brain stimulation (DBS) for Parkinson's disease (PD) one year after surgery and to create anatomical improvement maps based on patient-specific simulation of the electric field.

MATERIALS AND METHODS

We report the one-year results of bilateral cZi-DBS in 15 patients with PD. Patients were evaluated on/off medication and stimulation using the Unified Parkinson's Disease Rating Scale (UPDRS). Main outcomes were changes in motor symptoms (UPDRS-III) and quality of life according to Parkinson's Disease Questionnaire-39 (PDQ-39). Secondary outcomes included efficacy profile according to sub-items of UPDRS-III, and simulation of the electric field distribution around the DBS lead using the finite element method. Simulations from all patients were transformed to one common magnetic resonance imaging template space for creation of improvement maps and anatomical evaluation.

RESULTS

Median UPDRS-III score off medication improved from 40 at baseline to 21 on stimulation at one-year follow-up (48%, p < 0.0005). PDQ-39 summary index did not change but the subdomains activities of daily living (ADL) and stigma improved (25%, p < 0.03 and 75%, p < 0.01), whereas communication worsened (p < 0.03). For UPDRS-III sub-items, stimulation alone reduced median tremor score by 9 points, akinesia by 3, and rigidity by 2 points at one-year follow-up in comparison to baseline (90%, 25%, and 29% respectively, p < 0.01). Visual analysis of the anatomical improvement maps based on simulated electrical fields showed no evident relation with the degree of symptom improvement and neither did statistical analysis show any significant correlation.

CONCLUSIONS

Bilateral cZi-DBS alleviates motor symptoms, especially tremor, and improves ADL and stigma in PD patients one year after surgery. Improvement maps may be a useful tool for visualizing the spread of the electric field. However, there was no clear-cut relation between anatomical location of the electric field and the degree of symptom relief.

How accurately are subthalamic nucleus electrodes implanted relative to the ideal stimulation location for Parkinson's disease?

INTRODUCTION

The efficacy of subthalamic nucleus (STN) deep brain stimulation (DBS) in Parkinson's disease (PD) depends on how closely electrodes are implanted relative to an individual's ideal stimulation location. Yet, previous studies have assessed how closely electrodes are implanted relative to the planned location, after homogenizing data to a reference. Thus here, we measured how accurately electrodes are implanted relative to an ideal, dorsal STN stimulation location, assessed on each individual's native imaging. This measure captures not only the technical error of stereotactic implantation but also constraints imposed by planning a suitable trajectory.

METHODS

This cross-sectional study assessed 226 electrodes in 113 consecutive PD patients implanted with bilateral STN-DBS by experienced clinicians utilizing awake, microelectrode guided, surgery. The error (Euclidean distance) between the actual electrode trajectory versus a nominated ideal, dorsal STN stimulation location was determined in each hemisphere on native imaging and predictive factors sought.

RESULTS

The median electrode location error was 1.62 mm (IQR = 1.23 mm). This error exceeded 3 mm in 28/226 electrodes (12.4%). Location error did not differ between hemispheres implanted first or second, suggesting brain shift was minimised. Location error did not differ between electrodes positioned with (48/226), or without, a preceding microelectrode trajectory shift (suggesting such shifts were beneficial). There was no relationship between location error and case order, arguing against a learning effect.

DISCUSSION/CONCLUSION

The proximity of STN-DBS electrodes to a nominated ideal, dorsal STN, stimulation location is highly variable, even when implanted by experienced clinicians with brain shift minimized, and without evidence of a learning effect. Using this measure, we found that assessments on awake patients (microelectrode recordings and clinical examination) likely yielded beneficial intraoperative decisions to improve positioning. In many patients the error is likely to have reduced therapeutic efficacy. More accurate methods to implant STN-DBS electrodes relative to the ideal stimulation location are needed.

CLOVER-DBS: Algorithm-Guided Deep Brain Stimulation-Programming Based on External Sensor Feedback Evaluated in a Prospective, Randomized, Crossover, Double-Blind, Two-Center Study

BACKGROUND

Recent technological advances in deep brain stimulation (DBS) (e.g., directional leads, multiple independent current sources) lead to increasing DBS-optimization burden. Techniques to streamline and facilitate programming could leverage these innovations.

OBJECTIVE

We evaluated clinical effectiveness of algorithm-guided DBS-programming based on wearable-sensor-feedback compared to standard-of-care DBS-settings in a prospective, randomized, crossover, double-blind study in two German DBS centers.

METHODS

For 23 Parkinson's disease patients with clinically effective DBS, new algorithm-guided DBS-settings were determined and compared to previously established standard-of-care DBS-settings using UPDRS-III and motion-sensor-assessment. Clinical and imaging data with lead-localizations were analyzed to evaluate characteristics of algorithm-derived programming compared to standard-of-care. Six different versions of the algorithm were evaluated during the study and 10 subjects programmed with uniform algorithm-version were analyzed as a subgroup.

RESULTS

Algorithm-guided and standard-of-care DBS-settings effectively reduced motor symptoms compared to off-stimulation-state. UPDRS-III scores were reduced significantly more with standard-of-care settings as compared to algorithm-guided programming with heterogenous algorithm versions in the entire cohort. A subgroup with the latest algorithm version showed no significant differences in UPDRS-III achieved by the two programming-methods. Comparing active contacts in standard-of-care and algorithm-guided DBS-settings, contacts in the latter had larger location variability and were farther away from a literature-based optimal stimulation target.

CONCLUSION

Algorithm-guided programming may be a reasonable approach to replace monopolar review, enable less trained health-professionals to achieve satisfactory DBS-programming results, or potentially reduce time needed for programming. Larger studies and further improvements of algorithm-guided programming are needed to confirm these results.

Stimulation Sweet Spot in Subthalamic Deep Brain Stimulation - Myth or Reality? A Critical Review of Literature

INTRODUCTION

While deep brain stimulation (DBS) of the subthalamic nucleus (STN) has been extensively used for more than 20 years in Parkinson's disease (PD), the optimal area of stimulation to relieve motor symptoms remains elusive.

OBJECTIVE

We aimed at localizing the sweet spot within the subthalamic region by performing a systematic review of the literature.

METHOD

PubMed database was searched for published studies exploring optimal stimulation location for STN DBS in PD, published between 2000 and 2019. A standardized assessment procedure based on methodological features was applied to select high-quality publications. Studies conducted more than 3 months after the DBS procedure, employing lateralized scores and/or stimulation condition, and reporting the volume of tissue activated or the position of the stimulating contact within the subthalamic region were considered in the final analysis.

RESULTS

Out of 439 references, 24 were finally retained, including 21 studies based on contact location and 3 studies based on volume of tissue activated (VTA). Most studies (all VTA-based studies and 13 of the 21 contact-based studies) suggest the superior-lateral STN and the adjacent white matter as the optimal sites for stimulation. Remaining contact-based studies were either inconclusive (5/21), favoured the caudal zona incerta (1/21), or suggested a better outcome of STN stimulation than adjacent white matter stimulation (2/21).

CONCLUSION

Using a standardized methodological approach, our review supports the presence of a sweet spot located within the supero-lateral STN and extending to the adjacent white matter.

Evaluation of the Direct Effect of Bilateral Deep Brain Stimulation of the Subthalamic Nucleus on Levodopa-Induced On-Dyskinesia in Parkinson's Disease

Objective: This study aimed to evaluate the direct anti-dyskinesia effect of deep brain stimulation (DBS) of subthalamic nucleus (STN) on levodopa-induced on-dyskinesia in Parkinson's disease (PD) patients during the early period after surgery without reducing the levodopa dosage.

Methods: We retrospectively reviewed PD patients who underwent STN-DBS from January 2017 to October 2019 and enrolled patients with levodopa-induced on-dyskinesia before surgery and without a history of thalamotomy or pallidotomy. The Unified Dyskinesia Rating Scale (UDysRS) parts I+III+IV and the Unified Parkinson's Disease Rating Scale part III (UPDRS-III) were monitored prior to surgery, and at the 3-month follow-up, the location of active contacts was calculated by postoperative CT–MRI image fusion to identify stimulation sites with good anti-dyskinesia effect.

Results: There were 41 patients enrolled. The postoperative levodopa equivalent daily dose (LEDD) (823.1 ± 201.5 mg/day) was not significantly changed from baseline (844.6 ± 266.1 mg/day, P = 0.348), while the UDysRS on-dyskinesia subscores significantly decreased from 24 (10–58) to 0 (0–18) [median (range)] after STN stimulation (P < 0.0001). The levodopa-induced on-dyskinesia recurred in stimulation-off/medication-on state in all the 41 patients and disappeared in 39 patients when DBS stimulation was switched on at 3 months of follow-up. The active contacts which correspond to good effect for dyskinesia were located above the STN, and the mean coordinate was 13.05 ± 1.24 mm lateral, −0.13 ± 1.16 mm posterior, and 0.72 ± 0.78 mm superior to the midcommissural point.

Conclusions: High-frequency electrical stimulation of the area above the STN can directly suppress levodopa-induced on-dyskinesia.

Relationship between electrode position of deep brain stimulation and motor symptoms of Parkinson's disease

Background

To investigate the relationship between the position of bilateral STN-DBS location of active contacts and the clinical efficacy of STN-DBS on motor symptoms in Parkinson’s disease (PD) patients.

Methods

Retrospectively analyze the clinical data of 57 patients with PD who underwent bilateral STN-DBS from March 2018 to December 2018. Unified Parkinson’s Disease Rating Scale-Part III (UPDRS-III) score, levodopa equivalent day dose (LEDD), Parkinson’s Disease Quality of Life Scale (PDQ-39) before operation and within 6 months after operation, determine the location of activated contacts and volume of tissue activated (VTA) in the Montreal Neurological Institute (MNI) space, and analyze their correlation with the improvement rate of motor symptoms (UPDRS-III score improvement rate).

Results

After 6 months of follow up, the UPDRS-III scores of 57 patients (Med-off) were improved by 55.4 ± 18.9% (P<0.001) compared with that before operation. The improvement rate of PDQ-39 scores [(47.4 ± 23.2)%, (P < 0.001)] and the reduction rate of LEDD [(40.1 ± 24.3)%, (P < 0.01)] at 6 months postoperation were positively correlated with the improvement rate of motor symptoms (Med-off)(PDQ-39:r = 0.461, P<0.001; LEDD: r = 0.354, P = 0.007), the improvement rate of UPDRS-III (Med-off) and the Z-axis coordinate of the active contact in the MNI space were positively correlated (left side: r = 0.349,P = 0.008;right side: r = 0.369,P = 0.005). In the MNI space, there was no correlation between the UPDRS-III scores improvement rate (Med-off) at 6 months after operation and bilateral VTA in the STN motor subregion, STN associative subregion and STN limbic subregion of the active electrode contacts of 57 patients (all P > 0.05). At 6 months after surgery, the difference between the Z-axis coordinate in the different improvement rate subgroups(<25, 25 to 50%, and>50%) in the MNI space was statistically significant (left side: P = 0.030; right side: P = 0.024). In the MNI space, there was no statistically significant difference between the groups in the VTA of the electrode active contacts (all P > 0.05).

Conclusion

STN-DBS can improve the motor symptoms of PD patients and improve the quality of life. The closer the stimulation is to the STN dorsolateral sensorimotor area, the higher the DBS is to improve the motor symptoms of PD patients.

Modulation of beta bursts in subthalamic sensorimotor circuits predicts improvement in bradykinesia

No biomarker of Parkinson's disease exists that allows clinicians to adjust chronic therapy, either medication or deep brain stimulation, with real-time feedback. Consequently, clinicians rely on time-intensive, empirical, and subjective clinical assessments of motor behaviour and adverse events to adjust therapies. Accumulating evidence suggests that hypokinetic aspects of Parkinson's disease and their improvement with therapy are related to pathological neural activity in the beta band (beta oscillopathy) in the subthalamic nucleus. Additionally, effectiveness of deep brain stimulation may depend on modulation of the dorsolateral sensorimotor region of the subthalamic nucleus, which is the primary site of this beta oscillopathy. Despite the feasibility of utilizing this information to provide integrated, biomarker-driven precise deep brain stimulation, these measures have not been brought together in awake freely moving individuals. We sought to directly test whether stimulation-related improvements in bradykinesia were contingent on reduction of beta power and burst durations, and/or the volume of the sensorimotor subthalamic nucleus that was modulated. We recorded synchronized local field potentials and kinematic data in 16 subthalamic nuclei of individuals with Parkinson's disease chronically implanted with neurostimulators during a repetitive wrist-flexion extension task, while administering randomized different intensities of high frequency stimulation. Increased intensities of deep brain stimulation improved movement velocity and were associated with an intensity-dependent reduction in beta power and mean burst duration, measured during movement. The degree of reduction in this beta oscillopathy was associated with the improvement in movement velocity. Moreover, the reduction in beta power and beta burst durations was dependent on the theoretical degree of tissue modulated in the sensorimotor region of the subthalamic nucleus. Finally, the degree of attenuation of both beta power and beta burst durations, together with the degree of overlap of stimulation with the sensorimotor subthalamic nucleus significantly explained the stimulation-related improvement in movement velocity. The above results provide direct evidence that subthalamic nucleus deep brain stimulation-related improvements in bradykinesia are related to the reduction in beta oscillopathy within the sensorimotor region. With the advent of sensing neurostimulators, this beta oscillopathy combined with lead location could be used as a marker for real-time feedback to adjust clinical settings or to drive closed-loop deep brain stimulation in freely moving individuals with Parkinson's disease.

Probabilistic Mapping of Deep Brain Stimulation: Insights from 15 Years of Therapy

Deep brain stimulation (DBS) depends on precise delivery of electrical current to target tissues. However, the specific brain structures responsible for best outcome are still debated. We applied probabilistic stimulation mapping to a retrospective, multidisorder DBS dataset assembled over 15 years at our institution (n_total = 482 patients; n_{Parkinson disease} = 303; n_dystonia = 64; n_tremor = 39; n_{treatment-resistant depression/anorexia nervosa} = 76) to identify the neuroanatomical substrates of optimal clinical response. Using high-resolution structural magnetic resonance imaging and activation volume modeling, probabilistic stimulation maps (PSMs) that delineated areas of above-mean and below-mean response for each patient cohort were generated and defined in terms of their relationships with surrounding anatomical structures. Our results show that overlap between PSMs and individual patients' activation volumes can serve as a guide to predict clinical outcomes, but that this is not the sole determinant of response. In the future, individualized models that incorporate advancements in mapping techniques with patient-specific clinical variables will likely contribute to the optimization of DBS target selection and improved outcomes for patients. ANN NEUROL 2021;89:426-443.

Atlas-independent, N-of-1 tissue activation modeling to map optimal regions of subthalamic deep brain stimulation for Parkinson disease

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Neuroanatomical variations among patients are obscured in atlas-based VTA modeling.

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N-of-1 neuroanatomical and VTA modeling enables patient-level precision.

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Mean optimal stimulation is dorsomedial to the STN, near its posterior half.

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Individual VTAs deviate from optimal stimulation sites to varying degrees.

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Optimal stimulation sites for rigidity, bradykinesia, and tremor partially overlap.

Background

Motor outcomes after subthalamic deep brain stimulation (STN DBS) for Parkinson disease (PD) vary considerably among patients and strongly depend on stimulation location. The objective of this retrospective study was to map the regions of optimal STN DBS for PD using an atlas-independent, fully individualized (N-of-1) tissue activation modeling approach and to assess the relationship between patient-level therapeutic volumes of tissue activation (VTAs) and motor improvement.

Methods

The stimulation-induced electric field for 40 PD patients treated with bilateral STN DBS was modeled using finite element analysis. Neurostimulation models were generated for each patient, incorporating their individual STN anatomy, DBS lead position and orientation, anisotropic tissue conductivity, and clinical stimulation settings. A voxel-based analysis of the VTAs was then used to map the optimal location of stimulation. The amount of stimulation in specific regions relative to the STN was measured and compared between STNs with more and less optimal stimulation, as determined by their motor improvement scores and VTA. The relationship between VTA location and motor outcome was then assessed using correlation analysis. Patient variability in terms of STN anatomy, active contact position, and VTA location were also evaluated. Results from the N-of-1 model were compared to those from a simplified VTA model.

Results

Tissue activation modeling mapped the optimal location of stimulation to regions medial, posterior, and dorsal to the STN centroid. These regions extended beyond the STN boundary towards the caudal zona incerta (cZI). The location of the VTA and active contact position differed significantly between STNs with more and less optimal stimulation in the dorsal-ventral and anterior-posterior directions. Therapeutic stimulation spread noticeably more in the dorsal and posterior directions, providing additional evidence for cZI as an important DBS target. There were significant linear relationships between the amount of dorsal and posterior stimulation, as measured by the VTA, and motor improvement. These relationships were more robust than those between active contact position and motor improvement. There was high variability in STN anatomy, active contact position, and VTA location among patients. Spherical VTA modeling was unable to reproduce these results and tended to overestimate the size of the VTA.

Conclusion

Accurate characterization of the spread of stimulation is needed to optimize STN DBS for PD. High variability in neuroanatomy, stimulation location, and motor improvement among patients highlights the need for individualized modeling techniques. The atlas-independent, N-of-1 tissue activation modeling approach presented in this study can be used to develop and evaluate stimulation strategies to improve clinical outcomes on an individual basis.

Revisiting Forel Field Surgery

BACKGROUND

Lesioning the Forel field or the subthalamic region is considered a possible treatment for tremoric patients with Parkinson disease, essential tremor, and other diseases. This surgical treatment was performed in the 1960s to 1970s and was an alternative to thalamotomy. Recently, there has been increasing interest in the reappraisal of stimulating and/or lesioning these targets, partly as a result of innovations in imaging and noninvasive ablative technologies, such as magnetic resonance-guided focused ultrasonography.

OBJECTIVE

We wanted to perform a thorough review of the subthalamic region, both from an anatomic and a surgical standpoint, to offer a comprehensive and updated analysis of the techniques and results reported for patients with tremor treated with different techniques.

METHODS

We performed a systematic review of the literature, gathering articles that included patients who underwent ablative or stimulation surgical techniques, targeting the pallidothalamic pathways (pallidothalamic tractotomy), cerebellothalamic pathway (cerebellothalamic tractotomy), or subthalamic area.

RESULTS

Pallidothalamic tractotomy consists of a reduced area that includes pallidofugal pathways. It may be considered an interesting target, given the benefit/risk ratio and the clinical effect, which, compared with pallidotomy, involves a lower risk of injury or involvement of vital structures such as the internal capsule or optic tract. Cerebellothalamic tractotomy and/or posterior subthalamic area are other alternative targets to thalamic stimulation or ablative surgery.

CONCLUSIONS

Based on the significant breakthrough that magnetic resonance-guided focused ultrasonography has meant in the neurosurgical world, some classic targets such as the pallidothalamic tract, Forel field, and posterior subthalamic area may be reconsidered as surgical alternatives for patients with movement disorders.

The Medial Subthalamic Nucleus Border as a New Anatomical Reference in Stereotactic Neurosurgery for Parkinson's Disease

INTRODUCTION

The intersection of Bejjani's line with the well-delineated medial subthalamic nucleus (STN) border on MRI has recently been proposed as an individualized reference in subthalamic deep brain stimulation (DBS) surgery for Parkinson's disease (PD). We, therefore, aimed to investigate the applicability across centers of the medial STN border as a patient-specific reference point in STN DBS for PD and explore anatomical variability between left and right mesencephalic area within patients. Furthermore, we aim to evaluate a recently defined theoretic stimulation "hotspot" in a different center.

METHODS

Preoperative 3-Tesla T2 and susceptibility-weighted images (SWI) were used to identify the intersection of Bejjani's line with the medial STN border in left and right mesencephalic area. The average stereotactic coordinates of the center of stimulation relative to the medial STN border were compared with the predefined theoretic stimulation "hotspot."

RESULTS

Fifty-four patients provided 108 stereotactic coordinates of medial STN borders on both sequences. Significant difference in means was found in the Y-(anteroposterior) and Z-(dorsoventral) directions (T2 vs. SWI; p < 0.001). Mean coordinates in the Y-(anteroposterior) direction differed significantly between left and right mesencephalic area (T2: p < 0.001; SWI: p = 0.021). Sixty-six DBS leads were placed in 36 patients that had finished stimulation programming, and the average stereotactic coordinates of the center of stimulation relative to the medial STN border on T2 sequences were 3.1 mm lateral, 0.7 mm anterior, and 1.8 mm superior, in proximity of the predefined theoretic stimulation "hotspot."

CONCLUSION

The medial STN border is applicable across centers as a reference point for STN DBS surgery for PD and seems suitable in order to account for interindividual and intraindividual anatomical variability if one is aware of the discrepancies between T2-weighted imaging and SWI.

Parcellation of the Subthalamic Nucleus in Parkinson's Disease: A Retrospective Analysis of Atlas- and Diffusion-Based Methods

BACKGROUND

Deep brain stimulation (DBS) is an established method of treatment for Parkinson's disease (PD). A stimulation sweet spot at the interface between the motor and associative clusters of the subthalamic nucleus (STN) has recently been postulated. The aim of this study was to analyze the available clustering methods for the STN and their correlation to outcome.

METHODS

This is a retrospective analysis of a group of 20 patients implanted with a DBS device for PD. Atlas-based and diffusion tractography-based parcellation of the STN was performed. The distances of the electrode to the obtained clusters were compared to each other and to outcome parameters, which included levodopa equivalent dose (LED) reduction, Unified Parkinson's Disease Rating Scale (UPDRS)-III scores, and reduction in scores for items 32 and 36 of the UPDRS-IV.

RESULTS

The implanted electrodes were located nearest to the motor clusters of the STN. The following significant associations with postoperative LED reduction were found: (1) distance of the electrode to the motor cluster in the Accolla and DISTAL atlases (p < 0.01) and (2) distance of the electrode to the supplementary motor area cluster (p = 0.02). There was no association with either the UPDRS-III or the UPDRS-IV score.

CONCLUSIONS

The results of this study suggest the possibility that atlas-based clustering, as well as diffusion tractography-based parcellation, can be useful in estimating the stimulation target ("sweet spot") for STN-DBS in PD patients. Atlas-based as well as diffusion-based clustering might become a useful tool in DBS trajectory planning.

Impact of number of stimulation sites on long-lasting desynchronization effects of coordinated reset stimulation

Excessive neuronal synchrony is a hallmark of several neurological disorders, e.g., Parkinson's disease. An established treatment for medically refractory Parkinson's disease is high-frequency deep brain stimulation. However, it provides only acute relief, and symptoms return shortly after cessation of stimulation. A theory-based approach called coordinated reset (CR) has shown great promise in achieving long-lasting effects. During CR stimulation, phase-shifted stimuli are delivered to multiple stimulation sites to counteract neuronal synchrony. Computational studies in plastic neuronal networks reported that synaptic weights reduce during stimulation, which may cause sustained structural changes leading to stabilized desynchronized activity even after stimulation ceases. Corresponding long-lasting effects were found in recent preclinical and clinical studies. We study long-lasting desynchronization by CR stimulation in excitatory recurrent neuronal networks of integrate-and-fire neurons with spike-timing-dependent plasticity (STDP). We focus on the impact of the stimulation frequency and the number of stimulation sites on long-lasting effects. We compare theoretical predictions to simulations of plastic neuronal networks. Our results are important regarding CR calibration for two reasons. We reveal that long-lasting effects become most pronounced when stimulation parameters are adjusted to the characteristics of STDP-rather than to neuronal frequency characteristics. This is in contrast to previous studies where the CR frequency was adjusted to the dominant neuronal rhythm. In addition, we reveal a nonlinear dependence of long-lasting effects on the number of stimulation sites and the CR frequency. Intriguingly, optimal long-lasting desynchronization does not require larger numbers of stimulation sites.

Deep brain stimulation: Imaging on a group level

Deep Brain Stimulation (DBS) is an established treatment option for movement disorders and is under investigation for treatment in a growing number of other brain diseases. It has been shown that exact electrode placement crucially affects the efficacy of DBS and this should be considered when investigating novel indications or DBS targets. To measure clinical improvement as a function of electrode placement, neuroscientific methodology and specialized software tools are needed. Such tools should have the goal to make electrode placement comparable across patients and DBS centers, and include statistical analysis options to validate and define optimal targets. Moreover, to allow for comparability across different centers, these need to be performed within an algorithmically and anatomically standardized and openly available group space. With the publication of Lead-DBS software in 2014, an open-source tool was introduced that allowed for precise electrode reconstructions based on pre- and postoperative neuroimaging data. Here, we introduce Lead Group, implemented within the Lead-DBS environment and specifically designed to meet aforementioned demands. In the present article, we showcase the various processing streams of Lead Group in a retrospective cohort of 51 patients suffering from Parkinson's disease, who were implanted with DBS electrodes to the subthalamic nucleus (STN). Specifically, we demonstrate various ways to visualize placement of all electrodes in the group and map clinical improvement values to subcortical space. We do so by using active coordinates and volumes of tissue activated, showing converging evidence of an optimal DBS target in the dorsolateral STN. Second, we relate DBS outcome to the impact of each electrode on local structures by measuring overlap of stimulation volumes with the STN. Finally, we explore the software functions for connectomic mapping, which may be used to relate DBS outcomes to connectivity estimates with remote brain areas. The manuscript is accompanied by a walkthrough tutorial which allows users to reproduce all main results presented here. All data and code needed to reproduce results are openly available.

The impact of modern-day neuroimaging on the field of deep brain stimulation

PURPOSE OF REVIEW

Deep brain stimulation (DBS) is an established but growing treatment option for multiple brain disorders. Over the last decade, electrode placement and their effects were increasingly analyzed with modern-day neuroimaging methods like spatial normalization, fibertracking, or resting-state functional MRI. Similarly, specialized basal ganglia MRI sequences were introduced and imaging at high field strengths has become increasingly popular.

RECENT FINDINGS

To facilitate the process of precise electrode localizations, specialized software pipelines were introduced. By those means, DBS targets could recently be refined and significant relationships between electrode placement and clinical improvement could be shown. Furthermore, by combining electrode reconstructions with network imaging methods, relationships between electrode connectivity and clinical improvement were investigated. This led to a broad series of imaging-based insights about DBS that are reviewed in the present work.

SUMMARY

The reviewed literature makes a strong case that brain imaging plays an increasingly important role in DBS targeting and programming. Furthermore, brain imaging will likely help to better understand the mechanism of action of DBS.

Zona incerta as a therapeutic target in Parkinson's disease

The zona incerta has recently become an important target for deep-brain stimulation (DBS) in Parkinson's disease (PD). The present review summarizes clinical, animal and anatomical data which have indicated an important role of this structure in PD, and discusses potential mechanisms involved in therapeutic effects of DBS. Animal studies have suggested initially some role of neurons as well as GABAergic and glutamatergic receptors of the zona incerta in locomotion and generation of PD signs. Anatomical data have indicated that thanks to its multiple interconnections with the basal ganglia, thalamus, cerebral cortex, brainstem, spinal cord and cerebellum, the zona incerta is an important link in a neuronal chain transmitting impulses involved in PD pathology. Finally, clinical studies have shown that DBS of this structure alleviates parkinsonian bradykinesia, muscle rigidity and tremor. DBS of caudal zona incerta seemed to be the most effective therapeutic intervention, especially with regard to reduction of PD tremor as well as other forms of tremor.

White matter tracts involved by deep brain stimulation of the subthalamic nucleus in Parkinson's disease: a connectivity study based on preoperative diffusion tensor imaging tractography

Purpose: To depict the specific brain networks that are modulated by deep brain stimulation (DBS) of the subthalamic nucleus (STN) in Parkinson's disease (PD), using diffusion tensor imaging-based fibre tractography (DTI-FT).Materials and methods: Nine patients who received bilateral STN-DBS for PD were included. Electrodes were localized by co-registering preoperative magnetic resonance imaging and postoperative computed tomography. The volume of tissue activated (VTA) was estimated as an isotropic, spherical electric field distribution centred at each effective electrode contact's centroid coordinates, taking into account individual stimulation parameters (i.e. voltage, impedance). Brain connectivity analysis was undertaken using a deterministic DTI-FT method, seeded from a single region of interest corresponding to the VTA. The labelling of the reconstructed white matter fibre tracts relied on their path and (sub)cortical termination territories.Results: Six months after surgery, we observed a statistically significant reduction in both the Unified Parkinson Disease Rating Scale part III and L-dopa equivalent daily dose. Areas consistently connected to the VTA included the brainstem (100%), cerebellum (94%), dorsal (i.e. supplementary motor area) and lateral premotor cortex (94%), and primary motor cortex (72%). An involvement of the hyperdirect pathway (HDP) connecting the STN and the (pre)motor cortex was demonstrated.Conclusions: The connectivity patterns observed in this study suggest that the therapeutic effects of STN-DBS are mediated through the modulation of distributed, large-scale motor networks. Specifically, the depiction of projection neurons connecting the stimulated area/STN to the (pre)motor cortex, reinforce the growing evidence that the HDP might be a potential therapeutic target in PD. If further replicated, these findings could raise the possibility that DTI-FT reconstruction of the HDP may critically improve DBS targeting and stimulation parameters selection, through the development of programming tools that incorporate VTA modelling and patient-specific DTI-FT data.

Beta bursts during continuous movements accompany the velocity decrement in Parkinson's disease patients

Bradykinesia is reported to correlate with subthalamic beta power (13-35 Hz) recorded at rest in Parkinson's disease (PD). Pilot studies suggest adaptive deep brain stimulation triggered by amplitude threshold crossings of beta activity defined at rest is effective. This is puzzling, given that beta is suppressed during repetitive movements when bradykinesia becomes apparent. Recently, increased beta power in PD has been linked to beta bursts. Here we investigate whether beta bursts also occur during repetitive movements and relate to progressive decrement in movement velocity. Therefore, subthalamic local field potentials were recorded in 12 PD patients off medication while performing 30s blocks of rotatory movements alternating with rest periods. Bursts were defined separately for the low (13-20 Hz) and high (20-35 Hz) beta band using thresholds defined at rest. As expected, velocity significantly decreased within movement blocks. Despite the sustained suppression of both beta sub-bands, bursts could still be detected during movement. Beta bursts were reduced in amplitude, duration and rate during movement with beta rate correlating best with beta power. A mixed-effects linear model revealed that percentage time spent in beta bursts predicted velocity decreases better than averaged power. This correlation was specific for the low beta band. Our results link beta bursts during movement to bradykinesia. This helps explain how beta activity may contribute to bradykinetic movement decrement even though mean beta power is reduced during movement. Moreover, our findings help explain the effectiveness of adaptive DBS triggered off beta bursts, even though these may be defined with respect to beta levels at rest.

Deep Brain Stimulation Programming for Movement Disorders: Current Concepts and Evidence-Based Strategies

Deep brain stimulation (DBS) has become the treatment of choice for advanced stages of Parkinson's disease, medically intractable essential tremor, and complicated segmental and generalized dystonia. In addition to accurate electrode placement in the target area, effective programming of DBS devices is considered the most important factor for the individual outcome after DBS. Programming of the implanted pulse generator (IPG) is the only modifiable factor once DBS leads have been implanted and it becomes even more relevant in cases in which the electrodes are located at the border of the intended target structure and when side effects become challenging. At present, adjusting stimulation parameters depends to a large extent on personal experience. Based on a comprehensive literature search, we here summarize previous studies that examined the significance of distinct stimulation strategies for ameliorating disease signs and symptoms. We assess the effect of adjusting the stimulus amplitude (A), frequency (f), and pulse width (pw) on clinical symptoms and examine more recent techniques for modulating neuronal elements by electrical stimulation, such as interleaving (Medtronic®) or directional current steering (Boston Scientific®, Abbott®). We thus provide an evidence-based strategy for achieving the best clinical effect with different disorders and avoiding adverse effects in DBS of the subthalamic nucleus (STN), the ventro-intermedius nucleus (VIM), and the globus pallidus internus (GPi).

Effects of Deep Brain Stimulation of the Subthalamic Nucleus Settings on Voice Quality, Intensity, and Prosody in Parkinson’s Disease: Preliminary Evidence for Speech Optimization

Objective: To systematically evaluate how different deep brain stimulation of the subthalamic nucleus (STN-DBS) amplitude, frequency, and pulse-width electrical parameter settings impact speech intensity, voice quality, and prosody of speech in Parkinson’s disease (PD). Methods: Ten individuals with PD receiving bilateral STN-DBS treatments were seen for three baseline and five treatment visits. The five treatment visits involved an examination of the standard clinical settings as well as manipulation of different combinations of frequency (low, mid, and high), pulse width (low, mid, and high), and voltage (low, mid, and high) of stimulation. Measures of speech intensity, jitter, shimmer, harmonics–noise ratio, semitone standard deviation, and listener ratings of voice quality and prosody were obtained for each STN-DBS manipulation. Results: The combinations of lower frequency, lower pulse width, and higher voltage settings were associated with improved speech outcomes compared to the current standard clinical settings. In addition, decreased total electrical energy delivered to the STN appears to be associated with speech improvements. Conclusions: This study provides preliminary evidence that STN-DBS may be optimized for Parkinson-related problems with voice quality, speech intensity, and prosody of speech.

Electrode Location in a Microelectrode Recording-Based Model of the Subthalamic Nucleus Can Predict Motor Improvement After Deep Brain Stimulation for Parkinson's Disease

Motor improvement after deep brain stimulation (DBS) in the subthalamic nucleus (STN) may vary substantially between Parkinson’s disease (PD) patients. Research into the relation between improvement and active contact location requires a correction for anatomical variation. We studied the relation between active contact location relative to the neurophysiological STN, estimated by the intraoperative microelectrode recordings (MER-based STN), and contralateral motor improvement after one year. A generic STN shape was transformed to fit onto the stereotactically defined MER sites. The location of 43 electrodes (26 patients), derived from MRI-fused CT images, was expressed relative to this patient-specific MER-based STN. Using regression analyses, the relation between contact location and motor improvement was studied. The regression model that predicts motor improvement based on levodopa effect alone was significantly improved by adding the one-year active contact coordinates (R² change = 0.176, p = 0.014). In the combined prediction model (adjusted R² = 0.389, p < 0.001), the largest contribution was made by the mediolateral location of the active contact (standardized beta = 0.490, p = 0.002). With the MER-based STN as a reference, we were able to find a significant relation between active contact location and motor improvement. MER-based STN modeling can be used to complement imaging-based STN models in the application of DBS.

Toward Electrophysiology-Based Intelligent Adaptive Deep Brain Stimulation for Movement Disorders

Deep brain stimulation (DBS) represents one of the major clinical breakthroughs in the age of translational neuroscience. In 1987, Benabid and colleagues demonstrated that high-frequency stimulation can mimic the effects of ablative neurosurgery in Parkinson's disease (PD), while offering two key advantages to previous procedures: adjustability and reversibility. Deep brain stimulation is now an established therapeutic approach that robustly alleviates symptoms in patients with movement disorders, such as Parkinson's disease, essential tremor, and dystonia, who present with inadequate or adverse responses to medication. Currently, stimulation electrodes are implanted in specific target regions of the basal ganglia-thalamic circuit and stimulation pulses are delivered chronically. To achieve optimal therapeutic effect, stimulation frequency, amplitude, and pulse width must be adjusted on a patient-specific basis by a movement disorders specialist. The finding that pathological neural activity can be sampled directly from the target region using the DBS electrode has inspired a novel DBS paradigm: closed-loop adaptive DBS (aDBS). The goal of this strategy is to identify pathological and physiologically normal patterns of neuronal activity that can be used to adapt stimulation parameters to the concurrent therapeutic demand. This review will give detailed insight into potential biomarkers and discuss next-generation strategies, implementing advances in artificial intelligence, to further elevate the therapeutic potential of DBS by capitalizing on its modifiable nature. Development of intelligent aDBS, with an ability to deliver highly personalized treatment regimens and to create symptom-specific therapeutic strategies in real-time, could allow for significant further improvements in the quality of life for movement disorders patients with DBS that ultimately could outperform traditional drug treatment.

Lead-DBS v2: Towards a comprehensive pipeline for deep brain stimulation imaging

Deep brain stimulation (DBS) is a highly efficacious treatment option for movement disorders and a growing number of other indications are investigated in clinical trials. To ensure optimal treatment outcome, exact electrode placement is required. Moreover, to analyze the relationship between electrode location and clinical results, a precise reconstruction of electrode placement is required, posing specific challenges to the field of neuroimaging. Since 2014 the open source toolbox Lead-DBS is available, which aims at facilitating this process. The tool has since become a popular platform for DBS imaging. With support of a broad community of researchers worldwide, methods have been continuously updated and complemented by new tools for tasks such as multispectral nonlinear registration, structural/functional connectivity analyses, brain shift correction, reconstruction of microelectrode recordings and orientation detection of segmented DBS leads. The rapid development and emergence of these methods in DBS data analysis require us to revisit and revise the pipelines introduced in the original methods publication. Here we demonstrate the updated DBS and connectome pipelines of Lead-DBS using a single patient example with state-of-the-art high-field imaging as well as a retrospective cohort of patients scanned in a typical clinical setting at 1.5T. Imaging data of the 3T example patient is co-registered using five algorithms and nonlinearly warped into template space using ten approaches for comparative purposes. After reconstruction of DBS electrodes (which is possible using three methods and a specific refinement tool), the volume of tissue activated is calculated for two DBS settings using four distinct models and various parameters. Finally, four whole-brain tractography algorithms are applied to the patient's preoperative diffusion MRI data and structural as well as functional connectivity between the stimulation volume and other brain areas are estimated using a total of eight approaches and datasets. In addition, we demonstrate impact of selected preprocessing strategies on the retrospective sample of 51 PD patients. We compare the amount of variance in clinical improvement that can be explained by the computer model depending on the preprocessing method of choice. This work represents a multi-institutional collaborative effort to develop a comprehensive, open source pipeline for DBS imaging and connectomics, which has already empowered several studies, and may facilitate a variety of future studies in the field.