Connectivity profile of thalamic deep brain stimulation to effectively treat essential tremor

Modeling the volume of tissue activated in deep brain stimulation and its clinical influence: a review

Deep brain stimulation (DBS) is a neuromodulatory therapy that has been FDA approved for the treatment of various disorders, including but not limited to, movement disorders (e.g., Parkinson's disease and essential tremor), epilepsy, and obsessive-compulsive disorder. Computational methods for estimating the volume of tissue activated (VTA), coupled with brain imaging techniques, form the basis of models that are being generated from retrospective clinical studies for predicting DBS patient outcomes. For instance, VTA models are used to generate target-and network-based probabilistic stimulation maps that play a crucial role in predicting DBS treatment outcomes. This review defines the methods for calculation of tissue activation (or modulation) including ones that use heuristic and clinically derived estimates and more computationally involved ones that rely on finite-element methods and biophysical axon models. We define model parameters and provide a comparison of commercial, open-source, and academic simulation platforms available for integrated neuroimaging and neural activation prediction. In addition, we review clinical studies that use these modeling methods as a function of disease. By describing the tissue-activation modeling methods and highlighting their application in clinical studies, we provide the neural engineering and clinical neuromodulation communities with perspectives that may influence the adoption of modeling methods for future DBS studies.

Mapping Subcortico-Cortical Coupling-A Comparison of Thalamic and Subthalamic Oscillations

BACKGROUND

The ventral intermediate nucleus of the thalamus (VIM) is an effective target for deep brain stimulation in tremor patients. Despite its therapeutic importance, its oscillatory coupling to cortical areas has rarely been investigated in humans.

OBJECTIVES

The objective of this study was to identify the cortical areas coupled to the VIM in patients with essential tremor.

METHODS

We combined resting-state magnetoencephalography with local field potential recordings from the VIM of 19 essential tremor patients. Whole-brain maps of VIM-cortex coherence in several frequency bands were constructed using beamforming and compared with corresponding maps of subthalamic nucleus (STN) coherence based on data from 19 patients with Parkinson's disease. In addition, we computed spectral Granger causality.

RESULTS

The topographies of VIM-cortex and STN-cortex coherence were very similar overall but differed quantitatively. Both nuclei were coupled to the ipsilateral sensorimotor cortex in the high-beta band; to the sensorimotor cortex, brainstem, and cerebellum in the low-beta band; and to the temporal cortex, brainstem, and cerebellum in the alpha band. High-beta coherence to sensorimotor cortex was stronger for the STN (P = 0.014), whereas low-beta coherence to the brainstem was stronger for the VIM (P = 0.017). Although the STN was driven by cortical activity in the high-beta band, the VIM led the sensorimotor cortex in the alpha band.

CONCLUSIONS

Thalamo-cortical coupling is spatially and spectrally organized. The overall similar topographies of VIM-cortex and STN-cortex coherence suggest that functional connections are not necessarily unique to one subcortical structure but might reflect larger frequency-specific networks involving VIM and STN to a different degree. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

The role of the motor thalamus in deep brain stimulation for essential tremor

The advent of next-generation technology has significantly advanced the implementation and delivery of Deep Brain Stimulation (DBS) for Essential Tremor (ET), yet controversies persist regarding optimal targets and networks responsible for tremor genesis and suppression. This review consolidates key insights from anatomy, neurology, electrophysiology, and radiology to summarize the current state-of-the-art in DBS for ET. We explore the role of the thalamus in motor function and describe how differences in parcellations and nomenclature have shaped our understanding of the neuroanatomical substrates associated with optimal outcomes. Subsequently, we discuss how seminal studies have propagated the ventral intermediate nucleus (Vim)-centric view of DBS effects and shaped the ongoing debate over thalamic DBS versus stimulation in the posterior subthalamic area (PSA) in ET. We then describe probabilistic- and network-mapping studies instrumental in identifying the local and network substrates subserving tremor control, which suggest that the PSA is the optimal DBS target for tremor suppression in ET. Taken together, DBS offers promising outcomes for ET, with the PSA emerging as a better target for suppression of tremor symptoms. While advanced imaging techniques have substantially improved the identification of anatomical targets within this region, uncertainties persist regarding the distinct anatomical substrates involved in optimal tremor control. Inconsistent subdivisions and nomenclature of motor areas and other subdivisions in the thalamus further obfuscate the interpretation of stimulation results. While loss of benefit and habituation to DBS remain challenging in some patients, refined DBS techniques and closed-loop paradigms may eventually overcome these limitations.

Disbalanced recruitment of crossed and uncrossed cerebello-thalamic pathways during deep brain stimulation is predictive of delayed therapy escape in essential tremor

BACKGROUND

Thalamic deep brain stimulation (DBS) is an efficacious treatment for drug-resistant essential tremor (ET) and the dentato-rubro-thalamic tract (DRT) constitutes an important target structure. However, up to 40% of patients habituate and lose treatment efficacy over time, frequently accompanied by a stimulation-induced cerebellar syndrome. The phenomenon termed delayed therapy escape (DTE) is insufficiently understood. Our previous work showed that DTE clinically is pronounced on the non-dominant side and suggested that differential involvement of crossed versus uncrossed DRT (DRTx/DRTu) might play a role in DTE development.

METHODS

We retrospectively enrolled right-handed patients under bilateral thalamic DBS >12 months for ET from a cross-sectional study. They were characterized with the Fahn-Tolosa-Marin Tremor Rating Scale (FTMTRS) and Scale for the Assessment and Rating of Ataxia (SARA) scores at different timepoints. Normative fiber tractographic evaluations of crossed and uncrossed cerebellothalamic pathways and volume of activated tissue (VAT) studies together with [18F]Fluorodeoxyglucose positron emission tomography were applied.

RESULTS

A total of 29 patients met the inclusion criteria. Favoring DRTu over DRTx in the non-dominant VAT was associated with DTE (R2 = 0.4463, p < 0.01) and ataxia (R2 = 0.2319, p < 0.01). Moreover, increasing VAT size on the right (non-dominant) side was associated at trend level with more asymmetric glucose metabolism shifting towards the right (dominant) dentate nucleus.

CONCLUSION

Our results suggest that a disbalanced recruitment of DRTu in the non-dominant VAT induces detrimental stimulation effects on the dominant cerebellar outflow (together with contralateral stimulation) leading to DTE and thus hampering the overall treatment efficacy.

Cognitive outcomes in patients with essential tremor treated with deep brain stimulation: a systematic review

Introduction

Essential tremor (ET) is a common neurological disease. Deep brain stimulation (DBS) to the thalamic ventral intermediate nucleus (VIM) or the adjacent structures, such as caudal zona incerta/ posterior subthalamic area (cZi/PSA), can be effective in treating medication refractory tremor. However, it is not clear whether DBS can cause cognitive changes, in which domain, and to what extent if so.

Methods

We systematically searched PubMed and the Web of Science for available publications reporting on cognitive outcomes in patients with ET who underwent DBS following the PICO (population, intervention, comparators, and outcomes) concept. The PRISMA guideline for systematic reviews was applied.

Results

Twenty relevant articles were finally identified and included for review, thirteen of which were prospective (one also randomized) studies and seven were retrospective. Cognitive outcomes included attention, memory, executive function, language, visuospatial function, and mood-related variables. VIM and cZi/PSA DBS were generally well tolerated, although verbal fluency and language production were affected in some patients. Additionally, left-sided VIM DBS was associated with negative effects on verbal abstraction, word recall, and verbal memory performance in some patients.

Conclusion

Significant cognitive decline after VIM or cZi/PSA DBS in ET patients appears to be rare. Future prospective randomized controlled trials are needed to meticulously study the effect of the location, laterality, and stimulation parameters of the active contacts on cognitive outcomes while considering possible medication change post-DBS, timing, standard neuropsychological battery, practice effects, the timing of assessment, and effect size as potential confounders.

Dynamic functional changes upon thalamotomy in essential tremor depend on baseline brain morphometry

Patients with drug-resistant essential tremor (ET) may undergo Gamma Knife stereotactic radiosurgical thalamotomy (SRS-T), where the ventro-intermediate nucleus of the thalamus (Vim) is lesioned by focused beams of gamma radiations to induce clinical improvement. Here, we studied SRS-T impacts on left Vim dynamic functional connectivity (dFC, n = 23 ET patients scanned before and 1 year after intervention), and on surface-based morphometric brain features (n = 34 patients, including those from dFC analysis). In matched healthy controls (HCs), three dFC states were extracted from resting-state functional MRI data. In ET patients, state 1 spatial stability increased upon SRS-T (F1,22 = 19.13, p = 0.004). More frequent expression of state 3 over state 1 before SRS-T correlated with greater clinical recovery in a way that depended on the MR signature volume (t6 = 4.6, p = 0.004). Lower pre-intervention spatial variability in state 3 expression also did (t6 = - 4.24, p = 0.005) and interacted with the presence of familial ET so that these patients improved less (t6 = 4.14, p = 0.006). ET morphometric profiles showed significantly lower similarity to HCs in 13 regions upon SRS-T (z ≤ - 3.66, p ≤ 0.022), and a joint analysis revealed that before thalamotomy, morphometric similarity and states 2/3 mean spatial similarity to HCs were anticorrelated, a relationship that disappeared upon SRS-T (z ≥ 4.39, p < 0.001). Our results show that left Vim functional dynamics directly relates to upper limb tremor lowering upon intervention, while morphometry instead has a supporting role in reshaping such dynamics.

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.

Four-tract probabilistic tractography technique for target selection in essential tremor treatment with magnetic resonance-guided focused ultrasound

OBJECTIVES

Magnetic resonance-guided focused ultrasound (MRgFUS) thalamotomy is a novel, minimally invasive ablative treatment for essential tremor (ET). The use of a four-tract probabilistic tractography technique, targeting the intersection between the dentato-rubro-thalamic tracts (both decussating and non-decussating), while evaluating the corticospinal tract and the medial lemniscus, may obtain immediate clinical results with reduced adverse events. Our aim is to present our experience with the four-tract technique for patients undergoing ET treatment with MRgFUS.

METHODS

Retrospective analysis of a prospective database of consecutive patients undergoing ET treatment in a single center from February 2022 to February 2023. Procedural parameters were collected, and tremor improvement was assessed with the Clinical Rating Scale for Tremor (CRST) at baseline and at 3 and 6 months. Adverse events were also reported.

RESULTS

Forty-three patients (median age, 72 years [interquartile range, 66-76]; 22 females) were evaluated. Tremor improved significatively in all CRST subsections at 3 months, including the CRST part A + B treated hand tremor (22 [19-27] vs 4 [2-7], p < 0.001) and CRST part C (16 [13-19] vs 3 [1-4], p < 0.001). Differences persisted significant at 6 months. Adverse events were few (4.1% of paresthesias and 12.5% of objective gait disturbance at follow-up) and recorded as mild. The median number of sonications was 7 [6-8] and mean operative time 68.7 ± 24.2 min.

CONCLUSION

Our data show support for the feasibility and benefits of systematic targeting approach with four-tract probabilistic tractography for treating ET using MRgFUS.

CLINICAL RELEVANCE STATEMENT

An approach with four-tract probabilistic tractography for treating essential tremor (ET) patients with magnetic resonance-guided focused ultrasound decreases interindividual variability with good clinical outcomes, low number of sonications, few adverse effects, and short procedure times.

KEY POINTS

• The optimal target for the treatment of essential tremor with MR-guided focused ultrasound remains unknown. • Four-tract probabilistic tractography is a feasible technique that reduces interindividual variability, with good clinical results, few side effects, and short operative time. • The four-tract tractography approach can be performed using different MRI scanners and post-processing software in comparison with the initial description of the technique.

Deep brain stimulation for essential tremor versus essential tremor plus: should we target the same spot in the thalamus?

Background

Although ET is a phenomenologically heterogeneous condition, thalamic DBS appears to be equally effective across subtypes. We hypothesized stimulation sites optimized for individuals with essential tremor (ET) would differ from individuals with essential tremor plus syndrome (ET-plus). We examined group differences in optimal stimulation sites within the ventral thalamus and their overlap of with relevant white matter tracts. By capturing these differences, we sought to determine whether ET subtypes are associated with anatomically distinct neural pathways.

Methods

A retrospective chart review was conducted on ET patients undergoing VIM DBS at MUSC between 01/2012 and 02/2022. Clinical, demographic, neuroimaging, and DBS stimulation parameter data were collected. Clinical characteristics and pre-DBS videos were reviewed to classify ET and ET-plus cohorts. Patients in ET-plus cohorts were further divided into ET with dystonia, ET with ataxia, and ET with others. DBS leads were reconstructed using Lead-DBS and the volume of tissue activated (VTA) overlap was performed using normative connectomes. Tremor improvement was measured by reduction in a subscore of tremor rating scale (TRS) post-DBS lateralized to the more affected limb.

Results

Sixty-eight ET patients were enrolled after initial screening, of these 10 ET and 24 ET-plus patients were included in the final analyses. ET group had an earlier age at onset (p = 0.185) and underwent surgery at a younger age (p = 0.096). Both groups achieved effective tremor control. No significant differences were found in lead placement or VTA overlap within ventral thalamus. The VTA center of gravity (COG) in the ET-plus cohort was located dorsal to that of the ET cohort. No significant differences were found in VTA overlap with the dentato-rubral-thalamic (DRTT) tracts or the ansa lenticularis. Dystonia was more prevalent than ataxia in the ET-plus subgroups (n = 18 and n = 5, respectively). ET-plus with dystonia subgroup had a more medial COG compared to ET-plus with ataxia.

Conclusion

VIM DBS therapy is efficacious in patients with ET and ET-plus. There were no significant differences in optimal stimulation site or VTA overlap with white-matter tracts between ET, ET-plus and ET-plus subgroups.

Focused ultrasound thalamotomy for tremor treatment impacts the cerebello-thalamo-cortical network

High-intensity Magnetic Resonance-guided Focused Ultrasound (MRgFUS) is a recent, non-invasive line of treatment for medication-resistant tremor. We used MRgFUS to produce small lesions in the thalamic ventral intermediate nucleus (VIM), an important node in the cerebello-thalamo-cortical tremor network, in 13 patients with tremor-dominant Parkinson's disease or essential tremor. Significant tremor alleviation in the target hand ensued (t(12) = 7.21, p < 0.001, two-tailed), which was strongly associated with the functional reorganization of the brain's hand region with the cerebellum (r = 0.91, p < 0.001, one-tailed). This reorganization potentially reflected a process of normalization, as there was a trend of increase in similarity between the hand cerebellar connectivity of the patients and that of a matched, healthy control group (n = 48) after treatment. Control regions in the ventral attention, dorsal attention, default, and frontoparietal networks, in comparison, exhibited no association with tremor alleviation and no normalization. More broadly, changes in functional connectivity were observed in regions belonging to the motor, limbic, visual, and dorsal attention networks, largely overlapping with regions connected to the lesion targets. Our results indicate that MRgFUS is a highly efficient treatment for tremor, and that lesioning the VIM may result in the reorganization of the cerebello-thalamo-cortical tremor network.

Neuroimaging-based analysis of DBS outcomes in pediatric dystonia: Insights from the GEPESTIM registry

INTRODUCTION

Deep brain stimulation (DBS) is an established treatment in patients of various ages with pharmaco-resistant neurological disorders. Surgical targeting and postoperative programming of DBS depend on the spatial location of the stimulating electrodes in relation to the surrounding anatomical structures, and on electrode connectivity to a specific distribution pattern within brain networks. Such information is usually collected using group-level analysis, which relies on the availability of normative imaging resources (atlases and connectomes). Analysis of DBS data in children with debilitating neurological disorders such as dystonia would benefit from such resources, especially given the developmental differences in neuroimaging data between adults and children. We assembled pediatric normative neuroimaging resources from open-access datasets in order to comply with age-related anatomical and functional differences in pediatric DBS populations. We illustrated their utility in a cohort of children with dystonia treated with pallidal DBS. We aimed to derive a local pallidal sweetspot and explore a connectivity fingerprint associated with pallidal stimulation to exemplify the utility of the assembled imaging resources.

METHODS

An average pediatric brain template (the MNI brain template 4.5-18.5 years) was implemented and used to localize the DBS electrodes in 20 patients from the GEPESTIM registry cohort. A pediatric subcortical atlas, analogous to the DISTAL atlas known in DBS research, was also employed to highlight the anatomical structures of interest. A local pallidal sweetspot was modeled, and its degree of overlap with stimulation volumes was calculated as a correlate of individual clinical outcomes. Additionally, a pediatric functional connectome of 100 neurotypical subjects from the Consortium for Reliability and Reproducibility was built to allow network-based analyses and decipher a connectivity fingerprint responsible for the clinical improvements in our cohort.

RESULTS

We successfully implemented a pediatric neuroimaging dataset that will be made available for public use as a tool for DBS analyses. Overlap of stimulation volumes with the identified DBS-sweetspot model correlated significantly with improvement on a local spatial level (R = 0.46, permuted p = 0.019). The functional connectivity fingerprint of DBS outcomes was determined to be a network correlate of therapeutic pallidal stimulation in children with dystonia (R = 0.30, permuted p = 0.003).

CONCLUSIONS

Local sweetspot and distributed network models provide neuroanatomical substrates for DBS-associated clinical outcomes in dystonia using pediatric neuroimaging surrogate data. Implementation of this pediatric neuroimaging dataset might help to improve the practice and pave the road towards a personalized DBS-neuroimaging analyses in pediatric patients.

A structural magnetic resonance imaging review of clinical motor outcomes from deep brain stimulation in movement disorders

Patients with movement disorders treated by deep brain stimulation do not always achieve successful therapeutic alleviation of motor symptoms, even in cases where surgery is without complications. Magnetic resonance imaging (MRI) offers methods to investigate structural brain-related factors that may be predictive of clinical motor outcomes. This review aimed to identify features which have been associated with variability in clinical post-operative motor outcomes in patients with Parkinson's disease, dystonia, and essential tremor from structural MRI modalities. We performed a literature search for articles published between 1 January 2000 and 1 April 2022 and identified 5197 articles. Following screening through our inclusion criteria, we identified 60 total studies (39 = Parkinson's disease, 11 = dystonia syndromes and 10 = essential tremor). The review captured a range of structural MRI methods and analysis techniques used to identify factors related to clinical post-operative motor outcomes from deep brain stimulation. Morphometric markers, including volume and cortical thickness were commonly identified in studies focused on patients with Parkinson's disease and dystonia syndromes. Reduced metrics in basal ganglia, sensorimotor and frontal regions showed frequent associations with reduced motor outcomes. Increased structural connectivity to subcortical nuclei, sensorimotor and frontal regions was also associated with greater motor outcomes. In patients with tremor, increased structural connectivity to the cerebellum and cortical motor regions showed high prevalence across studies for greater clinical motor outcomes. In addition, we highlight conceptual issues for studies assessing clinical response with structural MRI and discuss future approaches towards optimizing individualized therapeutic benefits. Although quantitative MRI markers are in their infancy for clinical purposes in movement disorder treatments, structural features obtained from MRI offer the powerful potential to identify candidates who are more likely to benefit from deep brain stimulation and provide insight into the complexity of disorder pathophysiology.

Insights and opportunities for deep brain stimulation as a brain circuit intervention

Deep brain stimulation (DBS) is an effective treatment and has provided unique insights into the dynamic circuit architecture of brain disorders. This Review illustrates our current understanding of the pathophysiology of movement disorders and their underlying brain circuits that are modulated with DBS. It proposes principles of pathological network synchronization patterns like beta activity (13-35 Hz) in Parkinson's disease. We describe alterations from microscale including local synaptic activity via modulation of mesoscale hypersynchronization to changes in whole-brain macroscale connectivity. Finally, an outlook on advances for clinical innovations in next-generation neurotechnology is provided: from preoperative connectomic targeting to feedback controlled closed-loop adaptive DBS as individualized network-specific brain circuit interventions.

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.

Internal Capsule/Nucleus Accumbens Deep Brain Stimulation Increases Impulsive Decision Making in Obsessive-Compulsive Disorder

BACKGROUND

Deep brain stimulation of the anterior limb of the internal capsule (ALIC)/nucleus accumbens is an effective treatment in patients with obsessive-compulsive disorder but may increase impulsive behavior. We aimed to investigate how active stimulation alters subdomains of impulsive decision making and whether respective effects depend on the location of stimulation sites.

METHODS

We assessed 15 participants with obsessive-compulsive disorder performing the Cambridge Gambling Task during active and inactive ALIC/nucleus accumbens deep brain stimulation. Specifically, we determined stimulation-induced changes in risk adjustment and delay aversion. To characterize underlying neural pathways, we computed probabilistic stimulation maps and applied fiber filtering based on normative structural connectivity data to identify "hot" and "cold" spots/fibers related to changes in impulsive decision making.

RESULTS

Active stimulation significantly reduced risk adjustment while increasing delay aversion, both implying increased impulsive decision making. Changes in risk adjustment were robustly associated with stimulation sites located in the central ALIC and fibers connecting the thalamus and subthalamic nucleus with the medial and lateral prefrontal cortex. Both hot spots and fibers for changes in risk adjustment were robust to leave-one-out cross-validation. Changes in delay aversion were similarly associated with central ALIC stimulation, but validation hereof was nonsignificant.

CONCLUSIONS

Our findings provide experimental evidence that ALIC/nucleus accumbens stimulation increases impulsive decision making in obsessive-compulsive disorder. We show that changes in risk adjustment depend on the location of stimulation volumes and affected fiber bundles. The relationship between impulsive decision making and long-term clinical outcomes requires further investigation.

Distinct phenotypes of stimulation-induced dysarthria represent different cortical networks in STN-DBS

BACKGROUND

Deep brain stimulation of the subthalamic nucleus is an effective treatment of Parkinson's disease, yet it is often associated with a general deterioration of speech intelligibility. Clustering the phenotypes of dysarthria has been proposed as a strategy to tackle these stimulation-induced speech problems.

METHODS

In this study, we examine a cohort of 24 patients to test the real-life application of the proposed clustering and attempt to attribute the clusters to specific brain networks with two different approaches of connectivity analysis.

RESULTS

Both our data-driven and hypothesis-driven approaches revealed strong connections of variants of stimulation-induced dysarthria to brain regions that are known actors of motor speech control. We showed a strong connection between the spastic dysarthria type and the precentral gyrus and supplementary motor area, prompting a possible disruption of corticobulbar fibers. The connection between the strained voice dysarthria and more frontal areas hints toward a deeper disruption of the motor programming of speech production.

CONCLUSIONS

These results provide insights into the mechanism of stimulation-induced dysarthria in deep brain stimulation of the subthalamic nucleus and may guide reprogramming attempts for individual Parkinson's patients based on pathophysiological understanding of the affected networks.

Lateral cerebellothalamic tract activation underlies DBS therapy for Essential Tremor

BACKGROUND

While deep brain stimulation (DBS) therapy can be effective at suppressing tremor in individuals with medication-refractory Essential Tremor, patient outcome variability remains a significant challenge across centers. Proximity of active electrodes to the cerebellothalamic tract (CTT) is likely important in suppressing tremor, but how tremor control and side effects relate to targeting parcellations within the CTT and other pathways in and around the ventral intermediate (VIM) nucleus of thalamus remain unclear.

METHODS

Using ultra-high field (7T) MRI, we developed high-dimensional, subject-specific pathway activation models for 23 directional DBS leads. Modeled pathway activations were compared with post-hoc analysis of clinician-optimized DBS settings, paresthesia thresholds, and dysarthria thresholds. Mixed-effect models were utilized to determine how the six parcellated regions of the CTT and how six other pathways in and around the VIM contributed to tremor suppression and induction of side effects.

RESULTS

The lateral portion of the CTT had the highest activation at clinical settings (p < 0.05) and a significant effect on tremor suppression (p < 0.001). Activation of the medial lemniscus and posterior-medial CTT was significantly associated with severity of paresthesias (p < 0.001). Activation of the anterior-medial CTT had a significant association with dysarthria (p < 0.05).

CONCLUSIONS

This study provides a detailed understanding of the fiber pathways responsible for therapy and side effects of DBS for Essential Tremor, and suggests a model-based programming approach will enable more selective activation of lateral fibers within the CTT.

Pallidal neuromodulation of the explore/exploit trade-off in decision-making

Every decision that we make involves a conflict between exploiting our current knowledge of an action's value or exploring alternative courses of action that might lead to a better, or worse outcome. The sub-cortical nuclei that make up the basal ganglia have been proposed as a neural circuit that may contribute to resolving this explore-exploit 'dilemma'. To test this hypothesis, we examined the effects of neuromodulating the basal ganglia's output nucleus, the globus pallidus interna, in patients who had undergone deep brain stimulation (DBS) for isolated dystonia. Neuromodulation enhanced the number of exploratory choices to the lower value option in a two-armed bandit probabilistic reversal-learning task. Enhanced exploration was explained by a reduction in the rate of evidence accumulation (drift rate) in a reinforcement learning drift diffusion model. We estimated the functional connectivity profile between the stimulating DBS electrode and the rest of the brain using a normative functional connectome derived from heathy controls. Variation in the extent of neuromodulation induced exploration between patients was associated with functional connectivity from the stimulation electrode site to a distributed brain functional network. We conclude that the basal ganglia's output nucleus, the globus pallidus interna, can adaptively modify decision choice when faced with the dilemma to explore or exploit.

Connectomic Basis for Tremor Control in Stereotactic Radiosurgical Thalamotomy

BACKGROUND AND PURPOSE

Given the increased use of stereotactic radiosurgical thalamotomy and other ablative therapies for tremor, new biomarkers are needed to improve outcomes. Using resting-state fMRI and MR tractography, we hypothesized that a "connectome fingerprint" can predict tremor outcomes and potentially serve as a targeting biomarker for stereotactic radiosurgical thalamotomy.

MATERIALS AND METHODS

We evaluated 27 patients who underwent unilateral stereotactic radiosurgical thalamotomy for essential tremor or tremor-predominant Parkinson disease. Percentage postoperative improvement in the contralateral limb Fahn-Tolosa-Marin Clinical Tremor Rating Scale (TRS) was the primary end point. Connectome-style resting-state fMRI and MR tractography were performed before stereotactic radiosurgery. Using the final lesion volume as a seed, "connectivity fingerprints" representing ideal connectivity maps were generated as whole-brain R-maps using a voxelwise nonparametric Spearman correlation. A leave-one-out cross-validation was performed using the generated R-maps.

RESULTS

The mean improvement in the contralateral tremor score was 55.1% (SD, 38.9%) at a mean follow-up of 10.0 (SD, 5.0) months. Structural connectivity correlated with contralateral TRS improvement (r = 0.52; P  = .006) and explained 27.0% of the variance in outcome. Functional connectivity correlated with contralateral TRS improvement (r = 0.50; P  = .008) and explained 25.0% of the variance in outcome. Nodes most correlated with tremor improvement corresponded to areas of known network dysfunction in tremor, including the cerebello-thalamo-cortical pathway and the primary and extrastriate visual cortices.

CONCLUSIONS

Stereotactic radiosurgical targets with a distinct connectivity profile predict improvement in tremor after treatment. Such connectomic fingerprints show promise for developing patient-specific biomarkers to guide therapy with stereotactic radiosurgical thalamotomy.

Automated deep brain stimulation programming based on electrode location: a randomised, crossover trial using a data-driven algorithm

BACKGROUND

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is highly effective in controlling motor symptoms in patients with Parkinson's disease. However, correct selection of stimulation parameters is pivotal to treatment success and currently follows a time-consuming and demanding trial-and-error process. We aimed to assess treatment effects of stimulation parameters suggested by a recently published algorithm (StimFit) based on neuroimaging data.

METHODS

This double-blind, randomised, crossover, non-inferiority trial was carried out at Charité - Universitätsmedizin, Berlin, Germany, and enrolled patients with Parkinson's disease treated with directional octopolar electrodes targeted at the STN. All patients had undergone DBS programming according to our centre's standard of care (SoC) treatment before study recruitment. Based on perioperative imaging data, DBS electrodes were reconstructed and StimFit was applied to suggest optimal stimulation settings. Patients underwent motor assessments using the Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale part III (MDS-UPDRS-III) during OFF-medication and in OFF-stimulation and ON-stimulation states under both conditions, StimFit and SoC parameter settings. Patients were randomly assigned (1:1) to receive either StimFit-programmed DBS first and SoC-programmed DBS second, or SoC-programmed DBS first and StimFit-programmed DBS second. The allocation schedule was generated using a computerised random number generator. Both the rater and patients were masked to the sequence of SoC and StimFit stimulation conditions. All patients who participated in the study were included in the analysis. The primary endpoint of this study was the absolute mean difference between MDS-UPDRS-III scores under StimFit and SoC stimulation, with a non-inferiority margin of 5 points. The study was registered at the German Register for Clinical Trials (DRKS00023115), and is complete.

FINDINGS

Between July 10, 2020, and Oct 28, 2021, 35 patients were enrolled in the study; 18 received StimFit followed by SoC stimulation, and 17 received SoC followed by StimFit stimulation. Mean MDS-UPDRS-III scores improved from 47·3 (SD 17·1) at OFF-stimulation baseline to 24·7 (SD 12·4) and 26·3 (SD 12·4) under SoC and StimFit stimulation, respectively. Mean difference between motor scores was -1·6 (SD 7·1; 95% CI -4·0 to 0·9; superiority test p_superiority=0·20; n=35), establishing non-inferiority of StimFit stimulation at a margin of -5 points (non-inferiority test p_{non-inferiority}=0·0038). In six patients (17%), initial programming of StimFit settings resulted in acute side-effects and amplitudes were reduced until side-effects disappeared.

INTERPRETATION

Automated data-driven algorithms can predict stimulation parameters that lead to motor symptom control comparable to SoC treatment. This approach could significantly decrease the time necessary to obtain optimal treatment parameters.

FUNDING

Deutsche Forschungsgemeinschaft through NeuroCure Clinical Research Center and TRR 295.

Deep brain stimulation of the posterior subthalamic area as an alternative strategy for management of Holmes tremor: A case report and review of the literature

Background:

Holmes tremor is often refractory to medical treatment and deep brain stimulation of the ventralis intermedius nucleus of the thalamus (VIM-DBS) is the intervention of choice in controlling the tremor. Herein, we present a beneficial alternative strategy for the management of such situations, considering the posterior subthalamic area (PSA) as the target of stimulation.

Case Description:

We report a 57-year-old male with the right-sided tremor following a traumatic brain injury 20 years ago. He had been diagnosed with Holmes tremor that was not responsive to nonsurgical therapeutic options. When refractoriness confirmed, he became a candidate for VIM-DBS. During the operation, by performing macrostimulation with a maximum of 2 mA of amplitude, the tremor had no response to the stimulation of different tracts, and severe right hemi-body paresthesia occurred; therefore, we modified our approach and targeted the PSA, which resulted in satisfactory control of the tremor. The permanent lead was implanted into the left side PSA. At 1-year follow-up, the right side tremor was under complete control.

Conclusion:

Our case and other similar pieces of evidence are consistently indicating the potential regulatory effects of PSA-DBS in controlling the Holmes tremor as a feasible alternative strategy when VIM-DBS does not provide a satisfactory response. However, further studies with larger sample size are required to evaluate the long-term response and its possible long-term stimulation-related effects.

Deep Brain Stimulation for Pediatric Dystonia: A Review of the Literature and Suggested Programming Algorithm

Deep brain stimulation (DBS) is an established intervention for use in pediatric movement disorders, especially dystonia. Although multiple publications have provided guidelines for deep brain stimulation patient selection and programming in adults, there are no evidence-based or consensus statements published for pediatrics. The result is lack of standardized care and underutilization of this effective treatment. To this end, we assembled a focus group of 13 pediatric movement disorder specialists and 1 neurosurgeon experienced in pediatric deep brain stimulation to review recent literature and current practices and propose a standardized approach to candidate selection, implantation target site selection, and programming algorithms. For pediatric dystonia, we provide algorithms for (1) programming for initial session and follow-up sessions, and (2) troubleshooting side effects encountered during programming. We discuss common side effects, how they present, and recommendations for management. This topical review serves as a resource for movement disorders specialists interested in using deep brain stimulation for pediatric dystonia.

Clinical neuroscience and neurotechnology: An amazing symbiosis

In the last decades, clinical neuroscience found a novel ally in neurotechnologies, devices able to record and stimulate electrical activity in the nervous system. These technologies improved the ability to diagnose and treat neural disorders. Neurotechnologies are concurrently enabling a deeper understanding of healthy and pathological dynamics of the nervous system through stimulation and recordings during brain implants. On the other hand, clinical neurosciences are not only driving neuroengineering toward the most relevant clinical issues, but are also shaping the neurotechnologies thanks to clinical advancements. For instance, understanding the etiology of a disease informs the location of a therapeutic stimulation, but also the way stimulation patterns should be designed to be more effective/naturalistic. Here, we describe cases of fruitful integration such as Deep Brain Stimulation and cortical interfaces to highlight how this symbiosis between clinical neuroscience and neurotechnology is closer to a novel integrated framework than to a simple interdisciplinary interaction.

In vivo probabilistic atlas of white matter tracts of the human subthalamic area combining track density imaging and optimized diffusion tractography

The human subthalamic area is a region of high anatomical complexity, tightly packed with tiny fiber bundles. Some of them, including the pallidothalamic, cerebello-thalamic, and mammillothalamic tracts, are relevant targets in functional neurosurgery for various brain diseases. Diffusion-weighted imaging-based tractography has been suggested as a useful tool to map white matter pathways in the human brain in vivo and non-invasively, though the reconstruction of these specific fiber bundles is challenging due to their small dimensions and complex anatomy. To the best of our knowledge, a population-based, in vivo probabilistic atlas of subthalamic white matter tracts is still missing. In the present work, we devised an optimized tractography protocol for reproducible reconstruction of the tracts of subthalamic area in a large data sample from the Human Connectome Project repository. First, we leveraged the super-resolution properties and high anatomical detail provided by short tracks track-density imaging (stTDI) to identify the white matter bundles of the subthalamic area on a group-level template. Tracts identification on the stTDI template was also aided by visualization of histological sections of human specimens. Then, we employed this anatomical information to drive tractography at the subject-level, optimizing tracking parameters to maximize between-subject and within-subject similarities as well as anatomical accuracy. Finally, we gathered subject level tracts reconstructed with optimized tractography into a large-scale, normative population atlas. We suggest that this atlas could be useful in both clinical anatomy and functional neurosurgery settings, to improve our understanding of the complex morphology of this important brain region.

Patient-specific structural connectivity informs outcomes of responsive neurostimulation for temporal lobe epilepsy

OBJECTIVE

Responsive neurostimulation is an effective therapy for patients with refractory mesial temporal lobe epilepsy. However, clinical outcomes are variable, few patients become seizure-free, and the optimal stimulation location is currently undefined. The aim of this study was to quantify responsive neurostimulation in the mesial temporal lobe, identify stimulation-dependent networks associated with seizure reduction, and determine if stimulation location or stimulation-dependent networks inform outcomes.

METHODS

We modeled patient-specific volumes of tissue activated and created probabilistic stimulation maps of local regions of stimulation across a retrospective cohort of 22 patients with mesial temporal lobe epilepsy. We then mapped the network stimulation effects by seeding tractography from the volume of tissue activated with both patient-specific and normative diffusion-weighted imaging. We identified networks associated with seizure reduction across patients using the patient-specific tractography maps and then predicted seizure reduction across the cohort.

RESULTS

Patient-specific stimulation-dependent connectivity was correlated with responsive neurostimulation effectiveness after cross-validation (p = .03); however, normative connectivity derived from healthy subjects was not (p = .44). Increased connectivity from the volume of tissue activated to the medial prefrontal cortex, cingulate cortex, and precuneus was associated with greater seizure reduction.

SIGNIFICANCE

Overall, our results suggest that the therapeutic effect of responsive neurostimulation may be mediated by specific networks connected to the volume of tissue activated. In addition, patient-specific tractography was required to identify structural networks correlated with outcomes. It is therefore likely that altered connectivity in patients with epilepsy may be associated with the therapeutic effect and that utilizing patient-specific imaging could be important for future studies. The structural networks identified here may be utilized to target stimulation in the mesial temporal lobe and to improve seizure reduction for patients treated with responsive neurostimulation.

Brain Connectomics

A central tenet of modern neuroscience is the conceptualization of the brain as a collection of complex networks or circuits with a shift away from traditional "localizationist" theories. Connectomics seeks to unravel these brain networks and their role in the pathophysiology of neurologic diseases. This article discusses the science of connectomics with the examples of its potential role in clinical medicine and neuromodulation in multiple disorders, such as essential tremor, Parkinson's disease, obsessive-compulsive disorder, and epilepsy.

Subthalamic deep brain stimulation for refractory Gilles de la Tourette's syndrome: clinical outcome and functional connectivity

Background

Deep brain stimulation (DBS) is a promising novel approach for managing refractory Gilles de la Tourette’s syndrome (GTS). The subthalamic nucleus (STN) is the most common DBS target for treating movement disorders, and smaller case studies have reported the efficacy of bilateral STN-DBS treatment for relieving tic symptoms. However, management of GTS and treatment mechanism of STN-DBS in GTS remain to be elucidated.

Methods

Ten patients undergoing STN-DBS were included. Tics severity was evaluated using the Yale Global Tic Severity Scale. The severities of comorbid psychiatric symptoms of obsessive–compulsive behavior (OCB), attention-deficit/hyperactivity disorder, anxiety, and depression; social and occupational functioning; and quality of life were assessed. Volumes of tissue activated were used as seed points for functional connectivity analysis performed using a control dataset.

Results

The overall tics severity significantly reduced, with 62.9% ± 26.2% and 58.8% ± 27.2% improvements at the 6- and 12-months follow-up, respectively. All three patients with comorbid OCB showed improvement in their OCB symptoms at both the follow-ups. STN-DBS treatment was reasonably well tolerated by the patients with GTS. The most commonly reported side effect was light dysarthria. The stimulation effect of STN-DBS might regulate these symptoms through functional connectivity with the thalamus, pallidum, substantia nigra pars reticulata, putamen, insula, and anterior cingulate cortices.

Conclusions

STN-DBS was associated with symptomatic improvement in severe and refractory GTS without significant adverse events. The STN is a promising DBS target by stimulating both sensorimotor and limbic subregions, and specific brain area doses affect treatment outcomes.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00415-022-11266-w.

Advances in DBS Technology and Novel Applications: Focus on Movement Disorders

PURPOSE OF REVIEW

Deep brain stimulation (DBS) is an established treatment in several movement disorders, including Parkinson's disease, dystonia, tremor, and Tourette syndrome. In this review, we will review and discuss the most recent findings including but not limited to clinical evidence.

RECENT FINDINGS

New DBS technologies include novel hardware design (electrodes, cables, implanted pulse generators) enabling new stimulation patterns and adaptive DBS which delivers potential stimulation tailored to moment-to-moment changes in the patient's condition. Better understanding of movement disorders pathophysiology and functional anatomy has been pivotal for studying the effects of DBS on the mesencephalic locomotor region, the nucleus basalis of Meynert, the substantia nigra, and the spinal cord. Eventually, neurosurgical practice has improved with more accurate target visualization or combined targeting. A rising research domain emphasizes bridging neuromodulation and neuroprotection. Recent advances in DBS therapy bring more possibilities to effectively treat people with movement disorders. Future research would focus on improving adaptive DBS, leading more clinical trials on novel targets, and exploring neuromodulation effects on neuroprotection.

Which one is the superior target? A comparison and pooled analysis between posterior subthalamic area and ventral intermediate nucleus deep brain stimulation for essential tremor

Background/Aims

The efficacy and safety of posterior subthalamic area (PSA) and ventral intermediate nucleus (VIM) deep brain stimulation (DBS) in the treatment of essential tremor (ET) have not been compared in large‐scale studies. We conducted a secondary analysis to identify the superior target of ET‐DBS treatment.

Methods

PubMed, Embase, Cochrane Library, and Google Scholar were searched for relevant studies before September 2021. The tremor‐suppression efficacy and rate of stimulation‐related complications (SRCR) after PSA‐DBS and VIM‐DBS treating ET were quantitatively compared. Secondary outcomes, including tremor subitem scores and quality of life results, were also analyzed. Subgroup analyses were further conducted to stratify by follow‐up (FU) periods and stimulation lateralities. This study was registered in Open Science Framework (DOI: 10.17605/OSF.IO/7VJQ8).

Results

A total of 23 studies including 122 PSA‐DBS patients and 326 VIM‐DBS patients were analyzed. The average follow‐up time was 12.81 and 14.66 months, respectively. For the percentage improvement of total tremor rating scale (TRS) scores, PSA‐DBS was significantly higher, when compared to VIM‐DBS in the sensitivity analysis (p = 0.030) and main analysis (p = 0.043). The SRCR after VIM‐DBS was higher than that of PSA‐DBS (p = 0.022), and bilateral PSA‐DBS was significantly superior to both bilateral and unilateral VIM‐DBS (p = 0.001).

Conclusions

This study provided level IIIa evidence that PSA‐DBS was more effective and safer for ET than VIM‐DBS in 12–24 months, although both PSA‐DBS and VIM‐DBS were effective in suppressing tremor in ET patients. Further prospective large‐scale randomized clinical trials are warranted in the future.

A brain network for deep brain stimulation induced cognitive decline in Parkinson's disease

Deep brain stimulation is an effective treatment for Parkinson's disease but can be complicated by side-effects such as cognitive decline. There is often a delay before this side-effect is apparent and the mechanism is unknown, making it difficult to identify patients at risk or select appropriate deep brain stimulation settings. Here, we test whether connectivity between the stimulation site and other brain regions is associated with cognitive decline following deep brain stimulation. First, we studied a unique patient cohort with cognitive decline following subthalamic deep brain stimulation for Parkinson's disease (n = 10) where reprogramming relieved the side-effect without loss of motor benefit. Using resting state functional connectivity data from a large normative cohort (n = 1000), we computed connectivity between each stimulation site and the subiculum, an a priori brain region functionally connected to brain lesions causing memory impairment. Connectivity between deep brain stimulation sites and this same subiculum region was significantly associated with deep brain stimulation induced cognitive decline (P < 0.02). We next performed a data-driven analysis to identify connections most associated with deep brain stimulation induced cognitive decline. Deep brain stimulation sites causing cognitive decline (versus those that did not) were more connected to the anterior cingulate, caudate nucleus, hippocampus, and cognitive regions of the cerebellum (PFWE < 0.05). The spatial topography of this deep brain stimulation-based circuit for cognitive decline aligned with an a priori lesion-based circuit for memory impairment (P = 0.017). To begin translating these results into a clinical tool that might be used for deep brain stimulation programming, we generated a 'heat map' in which the intensity of each voxel reflects the connectivity to our cognitive decline circuit. We then validated this heat map using an independent dataset of Parkinson's disease patients in which cognitive performance was measured following subthalamic deep brain stimulation (n = 33). Intersection of deep brain stimulation sites with our heat map was correlated with changes in the Mattis dementia rating scale 1 year after lead implantation (r = 0.39; P = 0.028). Finally, to illustrate how this heat map might be used in clinical practice, we present a case that was flagged as 'high risk' for cognitive decline based on intersection of the patient's deep brain stimulation site with our heat map. This patient had indeed experienced cognitive decline and our heat map was used to select alternative deep brain stimulation parameters. At 14 days follow-up the patient's cognition improved without loss of motor benefit. These results lend insight into the mechanism of deep brain stimulation induced cognitive decline and suggest that connectivity-based heat maps may help identify patients at risk and who might benefit from deep brain stimulation reprogramming.

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.

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.

Use of probabilistic tractography to provide reliable distinction of the motor and sensory thalamus for prospective targeting during asleep deep brain stimulation

OBJECTIVE

Accurate electrode placement is key to effective deep brain stimulation (DBS). The ventral intermediate nucleus (VIM) of the thalamus is an established surgical target for the treatment of essential tremor (ET). Retrospective tractography-based analysis of electrode placement has associated successful outcomes with modulation of motor input to VIM, but no study has yet evaluated the feasibility and efficacy of prospective presurgical tractography-based targeting alone. Therefore, the authors sought to demonstrate the safety and efficacy of probabilistic tractography-based VIM targeting in ET patients and to perform a systematic comparison of probabilistic and deterministic tractography.

METHODS

Fourteen patients with ET underwent preoperative diffusion imaging. Probabilistic tractography was applied for preoperative targeting, and deterministic tractography was performed as a comparison between methods. Tractography was performed using the motor and sensory areas as initiation seeds, the ipsilateral thalamus as an inclusion mask, and the contralateral dentate nucleus as a termination mask. Tract-density maps consisted of voxels with 10% or less of the maximum intensity and were superimposed onto anatomical images for presurgical planning. Target planning was based on probabilistic tract-density images and indirect target coordinates. Patients underwent robotic image-guided, image-verified implantation of directional DBS systems. Postoperative tremor scores with and without DBS were recorded. The center of gravity and Dice similarity coefficients were calculated and compared between tracking methods.

RESULTS

Prospective probabilistic targeting of VIM was successful in all 14 patients. All patients experienced significant tremor reduction. Formal postoperative tremor scores were available for 9 patients, who demonstrated a mean 68.0% tremor reduction. Large differences between tracking methods were observed across patients. Probabilistic tractography-identified VIM fibers were more anterior, lateral, and superior than deterministic tractography-identified fibers, whereas probabilistic tractography-identified ventralis caudalis fibers were more posterior, lateral, and superior than deterministic tractography-identified fibers. Deterministic methods were unable to clearly distinguish between motor and sensory fibers in the majority of patients, but probabilistic methods produced distinct separation.

CONCLUSIONS

Probabilistic tractography-based VIM targeting is safe and effective for the treatment of ET. Probabilistic tractography is more precise than deterministic tractography for the delineation of VIM and the ventralis caudalis nucleus of the thalamus. Deterministic algorithms tended to underestimate separation between motor and sensory fibers, which may have been due to its limitations with crossing fibers. Larger studies across multiple centers are necessary to further validate this method.

Personalizing Deep Brain Stimulation Using Advanced Imaging Sequences

OBJECTIVE

With a growing appreciation for interindividual anatomical variability and patient-specific brain connectivity, advanced imaging sequences offer the opportunity to directly visualize anatomical targets for deep brain stimulation (DBS). The lack of quantitative evidence demonstrating their clinical utility, however, has hindered their broad implementation in clinical practice.

METHODS

Using fast gray matter acquisition T1 inversion recovery (FGATIR) sequences, the present study identified a thalamic hypointensity that holds promise as a visual marker in DBS. To validate the clinical utility of the identified hypointensity, we retrospectively analyzed 65 patients (26 female, mean age = 69.1 ± 12.7 years) who underwent DBS in the treatment of essential tremor. We characterized its neuroanatomical substrates and evaluated the hypointensity's ability to predict clinical outcome using stimulation volume modeling and voxelwise mapping. Finally, we determined whether the hypointensity marker could predict symptom improvement on a patient-specific level.

RESULTS

Anatomical characterization suggested that the identified hypointensity constituted the terminal part of the dentatorubrothalamic tract. Overlap between DBS stimulation volumes and the hypointensity in standard space significantly correlated with tremor improvement (R²  = 0.16, p = 0.017) and distance to hotspots previously reported in the literature (R²  = 0.49, p = 7.9e-4). In contrast, the amount of variance explained by other anatomical atlas structures was reduced. When accounting for interindividual neuroanatomical variability, the predictive power of the hypointensity increased further (R²  = 0.37, p = 0.002).

INTERPRETATION

Our findings introduce and validate a novel imaging-based marker attainable from FGATIR sequences that has the potential to personalize and inform targeting and programming in DBS for essential tremor. ANN NEUROL 2022;91:613-628.

Past, Present, and Future of Deep Brain Stimulation: Hardware, Software, Imaging, Physiology and Novel Approaches

Deep brain stimulation (DBS) has advanced treatment options for a variety of neurologic and neuropsychiatric conditions. As the technology for DBS continues to progress, treatment efficacy will continue to improve and disease indications will expand. Hardware advances such as longer-lasting batteries will reduce the frequency of battery replacement and segmented leads will facilitate improvements in the effectiveness of stimulation and have the potential to minimize stimulation side effects. Targeting advances such as specialized imaging sequences and “connectomics” will facilitate improved accuracy for lead positioning and trajectory planning. Software advances such as closed-loop stimulation and remote programming will enable DBS to be a more personalized and accessible technology. The future of DBS continues to be promising and holds the potential to further improve quality of life. In this review we will address the past, present and future of DBS.

Essential Tremor-Do We Have Better Therapeutics? A Review of Recent Advances and Future Directions

PURPOSE OF REVIEW

Essential tremor (ET) is a very common condition that significantly impacts quality of life. Current medical treatments are quite limited, and while surgical treatments like deep brain stimulation (DBS) can be very effective, they come with their own limitations as well as procedural risks. This article reviews updates on recent advances and future directions in the treatment of ET.

RECENT FINDINGS

A new generation of pharmacologic agents specifically designed for ET is in clinical trials. Advances in DBS technology continue to improve this therapy. MRI-guided focused ultrasound (MRgFUS) is now an approved noninvasive ablative treatment for ET that is effective and shows potential for continuing improvement. The first peripheral stimulation device for ET has also now been approved. This article reviews updates on the treatment of ET, encompassing pharmacologic agents in clinical trials, DBS, MRgFUS, and noninvasive stimulation therapies. Recent treatment advances and future directions of development show a great deal of promise for ET therapeutics.

Probabilistic mapping reveals optimal stimulation site in essential tremor

OBJECTIVE

To obtain individual clinical and neuroimaging data of patients undergoing Deep Brain Stimulation for essential tremor from five different European centers to identify predictors of outcome and to identify an optimal stimulation site.

METHODS

We analysed retrospectively baseline covariates, pre- and postoperative clinical tremor scores (12-month) as well as individual imaging data from 119 patients to obtain individual electrode positions and stimulation volumes. Individual imaging and clinical data was used to calculate a probabilistic stimulation map in normalized space using voxel-wise statistical analysis. Finally, we used this map to train a classifier to predict tremor improvement.

RESULTS

Probabilistic mapping of stimulation effects yielded a statistically significant cluster that was associated with a tremor improvement greater than 50%. This cluster of optimal stimulation extended from the posterior subthalamic area to the ventralis intermedius nucleus and coincided with a normative structural-connectivity-based cerebello-thalamic tract (CTT). The combined features "distance between the stimulation volume and the significant cluster" and "CTT activation" were used as a predictor of tremor improvement. This correctly classified a greater than 50% tremor improvement with a sensitivity of 89% and a specificity of 57%.

INTERPRETATION

Our multicentre ET probabilistic stimulation map identified an area of optimal stimulation along the course of the CTT. The results of this study are mainly descriptive until confirmed in independent datasets, ideally through prospective testing. This target will be made openly available and may be used to guide surgical planning and for computer-assisted programming of deep brain stimulation in the future. This article is protected by copyright. All rights reserved.

Deep brain stimulation for arm tremor: A randomized trial comparing two targets

OBJECTIVE

Deep brain stimulation (DBS) of the thalamic ventral intermediate nucleus (VIM) effectively suppresses arm tremor. Uncontrolled studies suggest the posterior subthalamic area (PSA) may be superior. We compared the intra-individual efficacy of VIM- versus PSA-DBS on tremor suppression and arm function.

METHODS

We performed a randomized, double-blind, crossover trial at Oslo University Hospital in patients (18-80 years) with isolated or combined action tremor affecting at least one arm. Four-contact DBS leads were implanted (bi- or unilaterally) with a trajectory to cover the VIM (upper two contacts) and PSA (lower two contacts). Patients were randomized (1:1 ratio) post-surgery to: Group 1, VIM-stimulation months 0-3 (period 1), then PSA-stimulation months 4-6 (period 2); Group 2, PSA-stimulation first, then VIM-stimulation. Primary endpoint was the difference in improvement from baseline to the end of the VIM- versus PSA-period in the sum of the dominant arm tremor scores of the Fahn-Tolosa-Marin Tremor Rating Scale (FTMTRS), items 5/6 + 10-14.

RESULTS

Forty-five patients were randomized to Group 1 (n = 23) or 2 (n = 22). In the primary endpoint per-protocol analysis (mixed model, n = 40), mean difference in the sum FTMTRS score improvement for the dominant arm was -2.65 points (95% CI -4.33 to -0.97; p = 0.002). The difference in favour of PSA stimulation was highly significant in period 2, but not period 1.

INTERPRETATION

Our randomized trial demonstrated that PSA stimulation provided superior tremor suppression compared with VIM stimulation. A period effect reducing tremor for up to three months in both groups was most likely attributed to a post-surgery stun effect. This article is protected by copyright. All rights reserved.

Targeting the vim by direct visualization of the cerebello-thalamo-cortical pathway in 3 T proton density MRI: correlation with focused ultrasound lesioning

Surgical targeting of the ventral intermediate nucleus of the thalamus (VIM) has been historically done using indirect strategies. Here we depict the cerebello-thalamo-cortical tract (CTCT) through 3 T proton density (PD) in a cohort of patients who underwent high-intensity focus ultrasound (HIFUS) thalamotomy. Forty-seven patients treated in our institution with MR-guided HIFUS VIM thalamotomy were included in this study. PD weighted 3 T MRI used for presurgical planning was compared with postoperative MRI obtained 1 month after surgery. Images were processed with ISTX software (Brain lab, Munich, Germany). The coordinates of the VIM lesion concerning the inter-commissural line (ICL) were annotated. Deterministic tractographies using three ROIs were used to verify the different tracts. The triangle seen in the 3 T PD sequence at the level of the mesencephalic-diencephalic junction was systematically recognized. The posterior angle of this triangle at the junction of the CTCT and the ZI was denominated as "point P." The area of this triangle corresponds to the posterior subthalamic area (PSA) harboring the Raprl fibers. The CTCT was visible from 1 to 2.5 mm below the ICL. The average center of the final HIFUS lesion (point F) was 11 mm from the medial thalamic border of the thalamus (14.9 mm from the midline), 6.4 mm anterior to PC, and 0.6 mm above the ICL. The FUS point was consistently 1-2 mm directly above point P. The anterior border of the external angle of this triangle (point P) can be used as an intraparenchymal point for targeting the ventral border of the VIM. Three ROIs placed in a single slice around this triangle are a fast way to originate tractography of the CTCT, lemniscus medialis, and pyramidal tract.

Analyzing the Effects of Parameters for Tremor Modulation via Phase-Locked Electrical Stimulation on a Peripheral Nerve

(1) Background: Non-invasive neuromodulation is a promising alternative to medication or deep-brain stimulation treatment for Parkinson's Disease or essential tremor. In previous work, we developed and tested a wearable system that modulates tremor via the non-invasive, electrical stimulation of peripheral nerves. In this article, we examine the proper range and the effects of various stimulation parameters for phase-locked stimulation. (2) Methods: We recruited nine participants with essential tremor. The subjects performed a bean-transfer task that mimics an eating activity to elicit kinetic tremor while using the wearable stimulation system. We examined the effects of stimulation with a fixed duty cycle, at different stimulation amplitudes and frequencies. The epochs of stimulation were locked to one of four phase positions of ongoing tremor, as measured with an accelerometer. We analyzed stimulation-evoked changes of the frequency and amplitude of tremor. (3) Results: We found that the higher tremor amplitude group experienced a higher rate of tremor power reduction (up to 65%) with a higher amplitude of stimulation when the stimulation was applied at the ±peak of tremor phase. (4) Conclusions: The stimulation parameter can be adjusted to optimize tremor reduction, and this study lays the foundation for future large-scale parameter optimization experiments for personalized peripheral nerve stimulation.

Deep brain stimulation effect on anterior pallidum reduces motor impulsivity in Parkinson's disease

BACKGROUND

Deep Brain Stimulation (DBS) of the subthalamic nucleus or globus pallidus internus is used to treat the motor symptoms of Parkinson's disease. The former can worsen impulsive and compulsive behaviors after controlling for the reduction of dopaminergic medications. However, the effect of pallidal DBS on such behaviors in PD patients is less clear.

OBJECTIVE/HYPOTHESIS

We hypothesized that greater stimulation spread to the pallidum with prefrontal connectivity would reduce motor impulsivity.

METHODS

Seven Parkinson's patients with stable globus pallidus internus DBS settings for 3 months, disease duration of 13 ± 1.3 years, and Montreal Cognitive Assessment of 26.8 ± 1.1 each had two stimulation settings defined based on reconstructions of lead placement and volume of tissue activation targeting either a dorsal or ventral position along the DBS electrode but still within the globus pallidus internus. Subjects performed a stop signal reaction time task with the DBS turned off vs. on in each of the defined stimulation settings, which was correlated with the degree of stimulation effect on pallidal subregions.

RESULTS

A shorter distance between the volume of tissue activation and the right prefrontally-connected GPi correlated with less impulsivity on the stop signal reaction time task (r = 0.69, p < 0.05). Greater volume of tissue activation overlap with the non-prefrontally-connected globus pallidus internus was associated with increased impulsivity.

CONCLUSION

These data can be leveraged to optimize DBS programming in PD patients with problematic impulsivity or in other disorders involving impulsive behaviors such as substance use disorders.

Toward personalized medicine in connectomic deep brain stimulation

At the group-level, deep brain stimulation leads to significant therapeutic benefit in a multitude of neurological and neuropsychiatric disorders. At the single-patient level, however, symptoms may sometimes persist despite "optimal" electrode placement at established treatment coordinates. This may be partly explained by limitations of disease-centric strategies that are unable to account for heterogeneous phenotypes and comorbidities observed in clinical practice. Instead, tailoring electrode placement and programming to individual patients' symptom profiles may increase the fraction of top-responding patients. Here, we propose a three-step, circuit-based framework with the aim of developing patient-specific treatment targets that address the unique symptom constellation prevalent in each patient. First, we describe how a symptom network target library could be established by mapping beneficial or undesirable DBS effects to distinct circuits based on (retrospective) group-level data. Second, we suggest ways of matching the resulting symptom networks to circuits defined in the individual patient (template matching). Third, we introduce network blending as a strategy to calculate optimal stimulation targets and parameters by selecting and weighting a set of symptom-specific networks based on the symptom profile and subjective priorities of the individual patient. We integrate the approach with published literature and conclude by discussing limitations and future challenges.

Closing the Loop With Cortical Sensing: The Development of Adaptive Deep Brain Stimulation for Essential Tremor Using the Activa PC+S

Deep Brain Stimulation (DBS) is an important tool in the treatment of pharmacologically resistant neurological movement disorders such as essential tremor (ET) and Parkinson's disease (PD). However, the open-loop design of current systems may be holding back the true potential of invasive neuromodulation. In the last decade we have seen an explosion of activity in the use of feedback to "close the loop" on neuromodulation in the form of adaptive DBS (aDBS) systems that can respond to the patient's therapeutic needs. In this paper we summarize the accomplishments of a 5-year study at the University of Washington in the use of neural feedback from an electrocorticography strip placed over the sensorimotor cortex. We document our progress from an initial proof of hardware all the way to a fully implanted adaptive stimulation system that leverages machine-learning approaches to simplify the programming process. In certain cases, our systems out-performed current open-loop approaches in both power consumption and symptom suppression. Throughout this effort, we collaborated with neuroethicists to capture patient experiences and take them into account whilst developing ethical aDBS approaches. Based on our results we identify several key areas for future work. "Graded" aDBS will allow the system to smoothly tune the stimulation level to symptom severity, and frequent automatic calibration of the algorithm will allow aDBS to adapt to the time-varying dynamics of the disease without additional input from a clinician. Additionally, robust computational models of the pathophysiology of ET will allow stimulation to be optimized to the nuances of an individual patient's symptoms. We also outline the unique advantages of using cortical electrodes for control and the remaining hardware limitations that need to be overcome to facilitate further development in this field. Over the course of this study we have verified the potential of fully-implanted, cortically driven aDBS as a feasibly translatable treatment for pharmacologically resistant ET.

Clinical applications of magnetic resonance imaging based functional and structural connectivity

Advances in computational neuroimaging techniques have expanded the armamentarium of imaging tools available for clinical applications in clinical neuroscience. Non-invasive, in vivo brain MRI structural and functional network mapping has been used to identify therapeutic targets, define eloquent brain regions to preserve, and gain insight into pathological processes and treatments as well as prognostic biomarkers. These tools have the real potential to inform patient-specific treatment strategies. Nevertheless, a realistic appraisal of clinical utility is needed that balances the growing excitement and interest in the field with important limitations associated with these techniques. Quality of the raw data, minutiae of the processing methodology, and the statistical models applied can all impact on the results and their interpretation. A lack of standardization in data acquisition and processing has also resulted in issues with reproducibility. This limitation has had a direct impact on the reliability of these tools and ultimately, confidence in their clinical use. Advances in MRI technology and computational power as well as automation and standardization of processing methods, including machine learning approaches, may help address some of these issues and make these tools more reliable in clinical use. In this review, we will highlight the current clinical uses of MRI connectomics in the diagnosis and treatment of neurological disorders; balancing emerging applications and technologies with limitations of connectivity analytic approaches to present an encompassing and appropriate perspective.

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.

A Unified Functional Network Target for Deep Brain Stimulation in Obsessive-Compulsive Disorder

BACKGROUND

Multiple deep brain stimulation (DBS) targets have been proposed for treating intractable obsessive-compulsive disorder (OCD). Here, we investigated whether stimulation effects of different target sites would be mediated by one common or several segregated functional brain networks.

METHODS

First, seeding from active electrodes of 4 OCD patient cohorts (N = 50) receiving DBS to anterior limb of the internal capsule or subthalamic nucleus zones, optimal functional connectivity profiles for maximal Yale-Brown Obsessive Compulsive Scale improvements were calculated and cross-validated in leave-one-cohort-out and leave-one-patient-out designs. Second, we derived optimal target-specific connectivity patterns to determine brain regions mutually predictive of clinical outcome for both targets and others predictive for either target alone. Functional connectivity was defined using resting-state functional magnetic resonance imaging data acquired in 1000 healthy participants.

RESULTS

While optimal functional connectivity profiles showed both commonalities and differences between target sites, robust cross-predictions of clinical improvements across OCD cohorts and targets suggested a shared network. Connectivity to the anterior cingulate cortex, insula, and precuneus, among other regions, was predictive regardless of stimulation target. Regions with maximal connectivity to these commonly predictive areas included the insula, superior frontal gyrus, anterior cingulate cortex, and anterior thalamus, as well as the original stereotactic targets.

CONCLUSIONS

Pinpointing the network modulated by DBS for OCD from different target sites identified a set of brain regions to which DBS electrodes associated with optimal outcomes were functionally connected-regardless of target choice. On these grounds, we establish potential brain areas that could prospectively inform additional or alternative neuromodulation targets for obsessive-compulsive disorder.