Optimal deep brain stimulation sites and networks for cervical vs. generalized dystonia.

Dystonia is a debilitating disease with few treatment options. One effective option is deep brain stimulation (DBS) to the internal pallidum. While cervical and generalized forms of isolated dystonia have been targeted with a common approach to the posterior third of the nucleus, large-scale investigations regarding optimal stimulation sites and potential network effects have not been carried out. Here, we retrospectively studied clinical results following DBS for cervical and generalized dystonia in a multicenter cohort of 80 patients. We model DBS electrode placement based on pre- and postoperative imaging and introduce an approach to map optimal stimulation sites to anatomical space. Second, we investigate which tracts account for optimal clinical improvements, when modulated. Third, we investigate distributed stimulation effects on a whole-brain functional connectome level. Our results show marked differences of optimal stimulation sites that map to the somatotopic structure of the internal pallidum. While modulation of the striatopallidofugal axis of the basal ganglia accounted for optimal treatment of cervical dystonia, modulation of pallidothalamic bundles did so in generalized dystonia. Finally, we show a common multisynaptic network substrate for both phenotypes in the form of connectivity to the cerebellum and somatomotor cortex. Our results suggest a brief divergence of optimal stimulation networks for cervical vs. generalized dystonia within the pallidothalamic loop that merge again on a thalamo-cortical level and share a common whole-brain network.

GPi-DBS-induced brain metabolic activation in cervical dystonia.

BACKGROUND: Deep brain stimulation (DBS) of the globus pallidus interna (GPi) is a highly efficacious treatment for cervical dystonia, but its mechanism of action is not fully understood. Here, we investigate the brain metabolic effects of GPi-DBS in cervical dystonia. METHODS: Eleven patients with GPi-DBS underwent brain 18F-fluorodeoxyglucose positron emission tomography imaging during stimulation on and off. Changes in regional brain glucose metabolism were investigated at the active contact location and across the whole brain. Changes in motor symptom severity were quantified using the Toronto Western Spasmodic Torticollis Rating Scale (TWSTRS), executive function using trail making test (TMT) and parkinsonism using Unified Parkinson's Disease Rating Scale (UPDRS). RESULTS: The mean (SD) best therapeutic response to DBS during the treatment was 81 (22)%. The TWSTRS score was 3.2 (3.9) points lower DBS on compared with off (p=0.02). At the stimulation site, stimulation was associated with increased metabolism, which correlated with DBS stimulation amplitude (r=0.70, p=0.03) but not with changes in motor symptom severity (p>0.9). In the whole brain analysis, stimulation increased metabolism in the GPi, subthalamic nucleus, putamen, primary sensorimotor cortex (PFDR<0.05). Acute improvement in TWSTRS correlated with metabolic activation in the sensorimotor cortex and overall treatment response in the supplementary motor area. Worsening of TMT-B score was associated with activation of the anterior cingulate cortex and parkinsonism with activation in the putamen. CONCLUSIONS: GPi-DBS increases metabolic activity at the stimulation site and sensorimotor network. The clinical benefit and adverse effects are mediated by modulation of specific networks.

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. ANN NEUROL 2022;91:585-601.

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.

Quantifying the Variability Associated with Postoperative Localization of Deep Brain Stimulation Electrodes.

INTRODUCTION: Computational models of deep brain stimulation (DBS) have become common tools in clinical research studies that attempt to establish correlations between stimulation locations in the brain and behavioral outcome measures. However, the accuracy of any patient-specific DBS model depends heavily upon accurate localization of the DBS electrodes within the anatomy, which is typically defined via co-registration of clinical CT and MRI datasets. Several different approaches exist for this challenging registration problem, and each approach will result in a slightly different electrode localization. The goal of this study was to better understand how different processing steps (e.g., cost-function masking, brain extraction, intensity remapping) affect the estimate of the DBS electrode location in the brain. METHODS: No "gold standard" exists for this kind of analysis, as the exact location of the electrode in the living human brain cannot be determined with existing clinical imaging approaches. However, we can estimate the uncertainty associated with the electrode position, which can be used to guide statistical analyses in DBS mapping studies. Therefore, we used high-quality clinical datasets from 10 subthalamic DBS subjects and co-registered their long-term postoperative CT with their preoperative surgical targeting MRI using 9 different approaches. The distances separating all of the electrode location estimates were calculated for each subject. RESULTS: On average, electrodes were located within a median distance of 0.57 mm (0.49-0.74) of one another across the different registration approaches. However, when considering electrode location estimates from short-term postoperative CTs, the median distance increased to 2.01 mm (1.55-2.78). CONCLUSIONS: The results of this study suggest that electrode location uncertainty needs to be factored into statistical analyses that attempt to define correlations between stimulation locations and clinical outcomes.

Freezing of gait in Parkinson's disease reflects a sudden derangement of locomotor network dynamics.

Freezing of gait is a disabling symptom of Parkinson's disease that causes a paroxysmal inability to generate effective stepping. The underlying pathophysiology has recently migrated towards a dysfunctional supraspinal locomotor network, but the actual network derangements during ongoing gait freezing are unknown. We investigated the communication between the cortex and the subthalamic nucleus, two main nodes of the locomotor network, in seven freely-moving subjects with Parkinson's disease with a novel deep brain stimulation device, which allows on-demand recording of subthalamic neural activity from the chronically-implanted electrodes months after the surgical procedure. Multisite neurophysiological recordings during (effective) walking and ongoing gait freezing were combined with kinematic measurements and individual molecular brain imaging studies. Patients walked in a supervised environment closely resembling everyday life challenges. We found that during (effective) walking, the cortex and subthalamic nucleus were synchronized in a low frequency band (4-13 Hz). In contrast, gait freezing was characterized in every patient by low frequency cortical-subthalamic decoupling in the hemisphere with less striatal dopaminergic innervation. Of relevance, this decoupling was already evident at the transition from normal (effective) walking into gait freezing, was maintained during the freezing episode, and resolved with recovery of the effective walking pattern. This is the first evidence for a decoding of the networked processing of locomotion in Parkinson's disease and suggests that freezing of gait is a 'circuitopathy' related to a dysfunctional cortical-subcortical communication. A successful therapeutic approach for gait freezing in Parkinson's disease should aim at directly targeting derangements of neural network dynamics.

Network localization of cervical dystonia based on causal brain lesions.

Cervical dystonia is a neurological disorder characterized by sustained, involuntary movements of the head and neck. Most cases of cervical dystonia are idiopathic, with no obvious cause, yet some cases are acquired, secondary to focal brain lesions. These latter cases are valuable as they establish a causal link between neuroanatomy and resultant symptoms, lending insight into the brain regions causing cervical dystonia and possible treatment targets. However, lesions causing cervical dystonia can occur in multiple different brain locations, leaving localization unclear. Here, we use a technique termed 'lesion network mapping', which uses connectome data from a large cohort of healthy subjects (resting state functional MRI, n = 1000) to test whether lesion locations causing cervical dystonia map to a common brain network. We then test whether this network, derived from brain lesions, is abnormal in patients with idiopathic cervical dystonia (n = 39) versus matched controls (n = 37). A systematic literature search identified 25 cases of lesion-induced cervical dystonia. Lesion locations were heterogeneous, with lesions scattered throughout the cerebellum, brainstem, and basal ganglia. However, these heterogeneous lesion locations were all part of a single functionally connected brain network. Positive connectivity to the cerebellum and negative connectivity to the somatosensory cortex were specific markers for cervical dystonia compared to lesions causing other neurological symptoms. Connectivity with these two regions defined a single brain network that encompassed the heterogeneous lesion locations causing cervical dystonia. These cerebellar and somatosensory regions also showed abnormal connectivity in patients with idiopathic cervical dystonia. Finally, the most effective deep brain stimulation sites for treating dystonia were connected to these same cerebellar and somatosensory regions identified using lesion network mapping. These results lend insight into the causal neuroanatomical substrate of cervical dystonia, demonstrate convergence across idiopathic and acquired dystonia, and identify a network target for dystonia treatment.

Probabilistic mapping of the antidystonic effect of pallidal neurostimulation: a multicentre imaging study.

Deep brain stimulation of the internal globus pallidus is a highly effective and established therapy for primary generalized and cervical dystonia, but therapeutic success is compromised by a non-responder rate of up to 25%, even in carefully-selected groups. Variability in electrode placement and inappropriate stimulation settings may account for a large proportion of this outcome variability. Here, we present probabilistic mapping data on a large cohort of patients collected from several European centres to resolve the optimal stimulation volume within the pallidal region. A total of 105 dystonia patients with pallidal deep brain stimulation were enrolled and 87 datasets (43 with cervical dystonia and 44 with generalized dystonia) were included into the subsequent 'normative brain' analysis. The average improvement of dystonia motor score was 50.5 ± 30.9% in cervical and 58.2 ± 48.8% in generalized dystonia, while 19.5% of patients did not respond to treatment (<25% benefit). We defined probabilistic maps of anti-dystonic effects by aggregating individual electrode locations and volumes of tissue activated (VTA) in normative atlas space and ranking voxel-wise for outcome distribution. We found a significant relation between motor outcome and the stimulation volume, but not the electrode location per se. The highest probability of stimulation induced motor benefit was found in a small volume covering the ventroposterior globus pallidus internus and adjacent subpallidal white matter. We then used the aggregated VTA-based outcome maps to rate patient individual VTAs and trained a linear regression model to predict individual outcomes. The prediction model showed robustness between the predicted and observed clinical improvement, with an r2 of 0.294 (P < 0.0001). The predictions deviated on average by 16.9 ± 11.6 % from observed dystonia improvements. For example, if a patient improved by 65%, the model would predict an improvement between 49% and 81%. Results were validated in an independent cohort of 10 dystonia patients, where prediction and observed benefit had a correlation of r2 = 0.52 (P = 0.02) and a mean prediction error of 10.3% (±8.9). These results emphasize the potential of probabilistic outcome brain mapping in refining the optimal therapeutic volume for pallidal neurostimulation and advancing computer-assisted planning and programming of deep brain stimulation.

Identifying therapeutic targets from spontaneous beneficial brain lesions.

Brain damage can occasionally result in paradoxical functional benefit, which could help identify therapeutic targets for neuromodulation. However, these beneficial lesions are rare and lesions in multiple different brain locations can improve the same symptom. Using a technique called lesion network mapping, we show that heterogeneous lesion locations resulting in tremor relief are all connected to common nodes in the cerebellum and thalamus, the latter of which is a proven deep brain stimulation target for tremor. These results suggest that lesion network mapping can identify the common substrate underlying therapeutic lesions and effective therapeutic targets. Ann Neurol 2018;83:153-157.

Cortical network fingerprints predict deep brain stimulation outcome in dystonia.

BACKGROUND: Deep brain stimulation (DBS) is an effective evidence-based therapy for dystonia. However, no unequivocal predictors of therapy responses exist. We investigated whether patients optimally responding to DBS present distinct brain network organization and structural patterns. METHODS: From a German multicenter cohort of 82 dystonia patients with segmental and generalized dystonia who received DBS implantation in the globus pallidus internus, we classified patients based on the clinical response 3 years after DBS. Patients were assigned to the superior-outcome group or moderate-outcome group, depending on whether they had above or below 70% motor improvement, respectively. Fifty-one patients met MRI-quality and treatment response requirements (mean age, 51.3 ± 13.2 years; 25 female) and were included in further analysis. From preoperative MRI we assessed cortical thickness and structural covariance, which were then fed into network analysis using graph theory. We designed a support vector machine to classify subjects for the clinical response based on individual gray-matter fingerprints. RESULTS: The moderate-outcome group showed cortical atrophy mainly in the sensorimotor and visuomotor areas and disturbed network topology in these regions. The structural integrity of the cortical mantle explained about 45% of the DBS stimulation amplitude for optimal response in individual subjects. Classification analyses achieved up to 88% of accuracy using individual gray-matter atrophy patterns to predict DBS outcomes. CONCLUSIONS: The analysis of cortical integrity, informed by group-level network properties, could be developed into independent predictors to identify dystonia patients who benefit from DBS. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Pulse duration settings in subthalamic stimulation for Parkinson's disease.

BACKGROUND: Stimulation parameters in deep brain stimulation (DBS) of the subthalamic nucleus for Parkinson's disease (PD) are rarely tested in double-blind conditions. Evidence-based recommendations on optimal stimulator settings are needed. Results from the CUSTOM-DBS study are reported, comparing 2 pulse durations. METHODS: A total of 15 patients were programmed using a pulse width of 30 µs (test) or 60 µs (control). Efficacy and side-effect thresholds and unified PD rating scale (UPDRS) III were measured in meds-off (primary outcome). The therapeutic window was the difference between patients' efficacy and side effect thresholds. RESULTS: The therapeutic window was significantly larger at 30 µs than 60 µs (P = ·0009) and the efficacy (UPDRS III score) was noninferior (P = .00008). INTERPRETATION: Subthalamic neurostimulation at 30 µs versus 60 µs pulse width is equally effective on PD motor signs, is more energy efficient, and has less likelihood of stimulation-related side effects. © 2017 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Progressive gait ataxia following deep brain stimulation for essential tremor: adverse effect or lack of efficacy?

Thalamic deep brain stimulation is a mainstay treatment for severe and drug-refractory essential tremor, but postoperative management may be complicated in some patients by a progressive cerebellar syndrome including gait ataxia, dysmetria, worsening of intention tremor and dysarthria. Typically, this syndrome manifests several months after an initially effective therapy and necessitates frequent adjustments in stimulation parameters. There is an ongoing debate as to whether progressive ataxia reflects a delayed therapeutic failure due to disease progression or an adverse effect related to repeated increases of stimulation intensity. In this study we used a multimodal approach comparing clinical stimulation responses, modelling of volume of tissue activated and metabolic brain maps in essential tremor patients with and without progressive ataxia to disentangle a disease-related from a stimulation-induced aetiology. Ten subjects with stable and effective bilateral thalamic stimulation were stratified according to the presence (five subjects) of severe chronic-progressive gait ataxia. We quantified stimulated brain areas and identified the stimulation-induced brain metabolic changes by multiple 18 F-fluorodeoxyglucose positron emission tomography performed with and without active neurostimulation. Three days after deactivating thalamic stimulation and following an initial rebound of symptom severity, gait ataxia had dramatically improved in all affected patients, while tremor had worsened to the presurgical severity, thus indicating a stimulation rather than disease-related phenomenon. Models of the volume of tissue activated revealed a more ventrocaudal stimulation in the (sub)thalamic area of patients with progressive gait ataxia. Metabolic maps of both patient groups differed by an increased glucose uptake in the cerebellar nodule of patients with gait ataxia. Our data suggest that chronic progressive gait ataxia in essential tremor is a reversible cerebellar syndrome caused by a maladaptive response to neurostimulation of the (sub)thalamic area. The metabolic signature of progressive gait ataxia is an activation of the cerebellar nodule, which may be caused by inadvertent current spread and antidromic stimulation of a cerebellar outflow pathway originating in the vermis. An anatomical candidate could be the ascending limb of the uncinate tract in the subthalamic area. Adjustments in programming and precise placement of the electrode may prevent this adverse effect and help fine-tuning deep brain stimulation to ameliorate tremor without negative cerebellar signs.

Intraoperative Thresholds for Capsular Stimulation Are Reliable for Chronic Pallidal Deep Brain Stimulation in Dystonia.

BACKGROUND: The threshold current for inducing muscle contractions by stimulation of pyramidal tract fibres adjacent to the globus pallidus internus (GPi) is, besides microelectrode recordings for the determination of nuclear boundaries, currently the only neurophysiological marker for intraoperative refinement of the anatomically planned target point for pallidal deep brain stimulation (GPi-DBS) in dystonia. OBJECTIVES: To determine the relationship between intraoperative thresholds for muscle contractions under general anaesthesia and postoperative thresholds in GPi-DBS. METHODS: Intraoperatively, current amplitude thresholds (120 µs, 130 Hz) were determined in 6 dystonic patients under general anaesthesia (through the uninsulated tip of the microelectrode guide tube). Postoperative localization of chronic stimulation electrodes by MRI and image fusion with the stereotactic planning determined the stimulation contact for comparing thresholds with intraoperative values. RESULTS: Current thresholds were 3.3 ± 0.8 mA intraoperatively (follow-up 0, FU0; n = 12), 2.9 ± 1.2 mA within 1 week after surgery (FU1; n = 12), and 3.5 ± 1.6 mA after 6-17 months (FU2; n = 8). FU0 and FU1 differed by trend, and FU1 and FU2 were significantly different (Friedman test, p = 0.0048; post hoc Dunn multiple comparison test, p < 0.05). FU0 and FU2 were not different. DISCUSSION: The threshold amplitude to induce tonic muscular contractions may constitute a valid approach of functionally refining the anatomically guided electrode placement in GPi-DBS for dystonia, because intraoperative values are predictive for postoperative thresholds with the chronically implanted neurostimulation system.

Parkinson's disease in GTP cyclohydrolase 1 mutation carriers.

GTP cyclohydrolase 1, encoded by the GCH1 gene, is an essential enzyme for dopamine production in nigrostriatal cells. Loss-of-function mutations in GCH1 result in severe reduction of dopamine synthesis in nigrostriatal cells and are the most common cause of DOPA-responsive dystonia, a rare disease that classically presents in childhood with generalized dystonia and a dramatic long-lasting response to levodopa. We describe clinical, genetic and nigrostriatal dopaminergic imaging ([(123)I]N-ω-fluoropropyl-2ß-carbomethoxy-3ß-(4-iodophenyl) tropane single photon computed tomography) findings of four unrelated pedigrees with DOPA-responsive dystonia in which pathogenic GCH1 variants were identified in family members with adult-onset parkinsonism. Dopamine transporter imaging was abnormal in all parkinsonian patients, indicating Parkinson's disease-like nigrostriatal dopaminergic denervation. We subsequently explored the possibility that pathogenic GCH1 variants could contribute to the risk of developing Parkinson's disease, even in the absence of a family history for DOPA-responsive dystonia. The frequency of GCH1 variants was evaluated in whole-exome sequencing data of 1318 cases with Parkinson's disease and 5935 control subjects. Combining cases and controls, we identified a total of 11 different heterozygous GCH1 variants, all at low frequency. This list includes four pathogenic variants previously associated with DOPA-responsive dystonia (Q110X, V204I, K224R and M230I) and seven of undetermined clinical relevance (Q110E, T112A, A120S, D134G, I154V, R198Q and G217V). The frequency of GCH1 variants was significantly higher (Fisher's exact test P-value 0.0001) in cases (10/1318 = 0.75%) than in controls (6/5935 = 0.1%; odds ratio 7.5; 95% confidence interval 2.4-25.3). Our results show that rare GCH1 variants are associated with an increased risk for Parkinson's disease. These findings expand the clinical and biological relevance of GTP cycloydrolase 1 deficiency, suggesting that it not only leads to biochemical striatal dopamine depletion and DOPA-responsive dystonia, but also predisposes to nigrostriatal cell loss. Further insight into GCH1-associated pathogenetic mechanisms will shed light on the role of dopamine metabolism in nigral degeneration and Parkinson's disease.

Multimodal neuroimaging to characterize symptom-specific networks in movement disorders.

Movement disorders, such as Parkinson's disease, essential tremor, and dystonia, are characterized by their predominant motor symptoms, yet diseases causing abnormal movement also encompass several other symptoms, including non-motor symptoms. Here we review recent advances from studies of brain lesions, neuroimaging, and neuromodulation that provide converging evidence on symptom-specific brain networks in movement disorders. Although movement disorders have traditionally been conceptualized as disorders of the basal ganglia, cumulative data from brain lesions causing parkinsonism, tremor and dystonia have now demonstrated that this view is incomplete. Several recent studies have shown that lesions causing a given movement disorder occur in heterogeneous brain locations, but disrupt common brain networks, which appear to be specific to each motor phenotype. In addition, findings from structural and functional neuroimaging in movement disorders have demonstrated that brain abnormalities extend far beyond the brain networks associated with the motor symptoms. In fact, neuroimaging findings in each movement disorder are strongly influenced by the constellation of patients' symptoms that also seem to map to specific networks rather than individual anatomical structures or single neurotransmitters. Finally, observations from deep brain stimulation have demonstrated that clinical changes, including both symptom improvement and side effects, are dependent on the modulation of large-scale networks instead of purely local effects of the neuromodulation. Combined, this multimodal evidence suggests that symptoms in movement disorders arise from distinct brain networks, encouraging multimodal imaging studies to better characterize the underlying symptom-specific mechanisms and individually tailor treatment approaches.

Validation and application of computer vision algorithms for video-based tremor analysis.

Tremor is one of the most common neurological symptoms. Its clinical and neurobiological complexity necessitates novel approaches for granular phenotyping. Instrumented neurophysiological analyses have proven useful, but are highly resource-intensive and lack broad accessibility. In contrast, bedside scores are simple to administer, but lack the granularity to capture subtle but relevant tremor features. We utilise the open-source computer vision pose tracking algorithm Mediapipe to track hands in clinical video recordings and use the resulting time series to compute canonical tremor features. This approach is compared to marker-based 3D motion capture, wrist-worn accelerometry, clinical scoring and a second, specifically trained tremor-specific algorithm in two independent clinical cohorts. These cohorts consisted of 66 patients diagnosed with essential tremor, assessed in different task conditions and states of deep brain stimulation therapy. We find that Mediapipe-derived tremor metrics exhibit high convergent clinical validity to scores (Spearman's ρ = 0.55-0.86, p≤ .01) as well as an accuracy of up to 2.60 mm (95% CI [-3.13, 8.23]) and ≤0.21 Hz (95% CI [-0.05, 0.46]) for tremor amplitude and frequency measurements, matching gold-standard equipment. Mediapipe, but not the disease-specific algorithm, was capable of analysing videos involving complex configurational changes of the hands. Moreover, it enabled the extraction of tremor features with diagnostic and prognostic relevance, a dimension which conventional tremor scores were unable to provide. Collectively, this demonstrates that current computer vision algorithms can be transformed into an accurate and highly accessible tool for video-based tremor analysis, yielding comparable results to gold standard tremor recordings.

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

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

Imaging the spin: Disentangling the core processes underlying mental rotation by network mapping of data from meta-analysis.

Research on the mental rotation task has sparked debate regarding the specific processes that underly the capability of humans to mentally rotate objects. The spread of reported brain activations suggests that mental rotation is subserved by a neural network circle. However, no common network has yet been found that uncovers the crucial processes underlying this ability. We aimed to identify the common network crucial for mental rotation by coordinate-based network mapping of previous neuroimaging findings in mental rotation. A meta-analysis revealed 710 peak activation coordinates from 42 fMRI studies in mental rotation, which include a total 844 participants. The coordinates were mapped to a normative functional connectome (n = 1000) to identify a network of connected regions. To account for experimental factors, we examined this network against two control tasks, action imitation and symbolic number processing. A common and crucial network for mental rotation, centring on dorsal premotor, superior parietal and inferior temporal lobes was revealed. This network, separated from other experimental aspects, suggests that the crucial processes underlying mental rotation are motor rotation, visuospatial processing, and higher order visual object recognition.