Parkinsonian Tremor Research Articles

Parkinson's Disease Tremor Differentially Responds to Levodopa and Subthalamic Stimulation.

Tremor in Parkinson's disease (PD) has an inconsistent response to levodopa and subthalamic deep brain stimulation (STN-DBS). To identify predictive factors of PD tremor responsiveness to levodopa and STN-DBS. PD patients with upper limb tremor who underwent STN-DBS were included. The levodopa responsiveness of tremor (overall, postural, and rest sub-components), was assessed using the relevant Unified Parkinson's Disease Rating Scale-III items performed during the preoperative assessment. Post-surgical outcomes were similarly assessed ON and OFF stimulation. A score for the rest/postural tremor ratio was used to determine the influence of rest and postural tremor severity on STN-DBS outcome. Factors predictive of tremor responsiveness were determined using multiple linear regression modeling. Volume of tissue activated measurement coupled to voxel-based analysis was performed to identify anatomical clusters associated with motor symptoms improvement. One hundred and sixty five patients were included in this study. Male gender was negatively correlated with tremor responsiveness to levodopa, whereas the ratio of rest/postural tremor was positively correlated with both levodopa responsiveness and STN-DBS tremor outcome. Clusters corresponding to improvement of tremor were in the subthalamic nucleus, the zona incerta and the thalamus, whereas clusters corresponding to improvement for akinesia and rigidity were located within the subthalamic nucleus. More severe postural tremor and less severe rest tremor were associated with both poorer levodopa and STN-DBS response. The different locations of clusters associated with best correction of tremor and other parkinsonian features suggest that STN-DBS effect on PD symptoms is underpinned by the modulation of different networks.

Frameless LINAC-Based Stereotactic Radiosurgery is Safe and Effective for Essential and Parkinsonian Tremor

Stereotactic radiosurgery (SRS) to the thalamus is an ablative technique used for treatment of refractory tremor of essential or Parkinsonian origin. Because of the high dose, small target, and required precision, framed SRS on the Gamma Knife has been the historical platform of choice. We tested our recently developed technique to emulate GK dose distributions on a multi-leaf collimator (MLC)-equipped linear accelerator (LINAC) without cumbersome, inefficient cones in a prospective trial of safety and efficacy. We quantified pre-treatment contralateral tremor according to FTM scoring system. We obtained MPRAGE, FGATIR, DTI, and RS-fMRI sequences. We identified the VIM via classical stereotactic reference location and connectomically, and then targeted it to 135 Gy dmax in a manner dosimetrically roughly equivalent to 4 mm GK shot. We adjusted each target such that the 25 Gy isodose line did not overlap the posterior limb of the capsule. We immobilized patients in a highly rigid thermoplastic mask and delivered treatment on an Edge™ LINAC with HDMLC. Intrafraction optical surface monitoring (OSMS) ensured patient immobility. We surveilled post-treatment imaging and recorded tremor scoring, QOL outcomes, and adverse events. We accrued 42 patients (16 female, 26 males; median age 72.5) over 36 months. 38 had essential tremor, 4 had tremor-dominant Parkinson's; 2 withdrew prior to treatment. Ten patients were on therapeutic anti-coagulation, and were not required to discontinue. At time of submission 39 patients had follow-up ≥ 6 months. 35/39 (89.7%) exhibited clinically meaningful tremor reduction. Mean limb tremor reduction among responders was 43.5% (range: 9 - 100%). Time to patient-reported tremor improvement was 0.3 to 15 months. One patient experienced Gr 3, and 4 patients experienced Gr 1-2 toxicity. MLC-based SRS thalamotomy is safe and effective for refractory tremor treatment. Multidisciplinary management is key for proper patient selection, treatment, and monitoring. Our outcomes appear congruent to historical GK controls as well as more modern MRgFUS outcomes.

Neuronal Encoding of Speech Features in the Human Thalamus in Parkinson's Disease and Essential Tremor Patients.

The human thalamus is known, from stimulation studies and functional imaging, to participate in high-level language tasks. The goal of this study is to find whether and how speech features, in particular, vowel phonemes, are encoded in the neuronal activity of the thalamus, and specifically of the left ventralis intermediate nucleus (Vim), during speech production, perception, and imagery. In this cross-sectional study, we intraoperatively recorded single neuron activity in the left Vim of eight neurosurgical patients with Parkinson's disease (PD) (n = 4) or essential tremor (n = 4) undergoing implantation of deep brain stimulation (n = 3) or radiofrequency lesioning (n = 5) while patients articulated the five monophthongal vowel sounds. In this article, we report that single neurons in the left Vim encode individual vowel phonemes mainly during speech production but also during perception and imagery. They mainly use one of two encoding schemes: broad or sharp tuning, with a similar percentage of units each. Sinusoidal tuning has been demonstrated in almost half of the broadly tuned units. Patients with PD had a lower percentage of speech-related units in each aspect of speech (production, perception, and imagery), a significantly lower percentage of broadly tuned units, and significantly lower median firing rates during speech production and perception, but significantly higher rates during imagery, than patients with essential tremor. The results suggest that the left Vim uses mixed encoding schemes for speech features. Our findings explain, at the single neuron level, why deep brain stimulation and radiofrequency lesioning of the left Vim are likely to cause speech side effects. Moreover, they may indicate that speech-related units in the left Vim of patients with PD may be degraded even in the subclinical phase.

Development of a New Wearable Device for the Characterization of Hand Tremor.

Rest tremor (RT) is observed in subjects with Parkinson's disease (PD) and Essential Tremor (ET). Electromyography (EMG) studies have shown that PD subjects exhibit alternating contractions of antagonistic muscles involved in tremors, while the contraction pattern of antagonistic muscles is synchronous in ET subjects. Therefore, the RT pattern can be used as a potential biomarker for differentiating PD from ET subjects. In this study, we developed a new wearable device and method for differentiating alternating from a synchronous RT pattern using inertial data. The novelty of our approach relies on the fact that the evaluation of synchronous or alternating tremor patterns using inertial sensors has never been described so far, and current approaches to evaluate the tremor patterns are based on surface EMG, which may be difficult to carry out for non-specialized operators. This new device, named "RT-Ring", is based on a six-axis inertial measurement unit and a Bluetooth Low-Energy microprocessor, and can be worn on a finger of the tremulous hand. A mobile app guides the operator through the whole acquisition process of inertial data from the hand with RT, and the prediction of tremor patterns is performed on a remote server through machine learning (ML) models. We used two decision tree-based algorithms, XGBoost and Random Forest, which were trained on features extracted from inertial data and achieved a classification accuracy of 92% and 89%, respectively, in differentiating alternating from synchronous tremor segments in the validation set. Finally, the classification response (alternating or synchronous RT pattern) is shown to the operator on the mobile app within a few seconds. This study is the first to demonstrate that different electromyographic tremor patterns have their counterparts in terms of rhythmic movement features, thus making inertial data suitable for predicting the muscular contraction pattern of tremors.

The Clinical Profile of Tremor in Parkinson's Disease.

Tremor is one of the most troublesome manifestations of Parkinson's Disease (PD) and its response to dopaminergic medication is variable; an evidence-based framework of PD tremor is lacking yet needed to inform future investigations. To perform a comprehensive longitudinal analysis on the clinical characteristics, course and response to dopaminergic medication of tremor in de-novo PD. Three hundred ninety-seven participants were recruited in the Parkinson Progressive Markers Initiative, a prospective observational cohort study in early de-novo PD. Rest, postural and kinetic tremor scores were extracted from the Movement Disorders Society-Unified Parkinson's Disease Rating Scale. Progression from baseline to 7-year follow-up of rest, postural and kinetic tremor scores, and their response to in-clinic dopaminergic medication were analyzed through linear mixed-effects models adjusted for age, sex and disease duration at enrollment. A sensitivity analysis was conducted through subgroup and imputation analyses. 382 (96.2%) participants showed tremor and 346 (87.2%) showed rest tremor in at least one assessment over 7 years. Off-state rest, postural and kinetic tremor scores increased significantly over time, coupled with a significant effect of dopaminergic medication in reducing tremor scores. However, at each assessment, tremor was unresponsive to in-clinic dopaminergic medication in at least 20% of participants for rest, 30% for postural and 38% for kinetic tremor. PD tremor is a troublesome manifestation, with increasing severity and variable response to medications. This analysis details the current clinical natural history of tremor in early-to-mid stage PD, outlining an evidence-based framework for future pathophysiological and interventional studies.

Cerebellar and cerebral white matter changes in Parkinson's disease with resting tremor.

Cerebellum modulates the amplitude of resting tremor in Parkinson's disease (PD) via cerebello-thalamo-cortical (CTC) circuit. Tremor-related white matter alterations have been identified in PD patients by pathological studies, but in vivo evidence is limited; the influence of such cerebellar white matter alterations on tremor-related brain network, including CTC circuit, is also unclear. In this study, we investigated the cerebral and cerebellar white matter alterations in PD patients with resting tremor using diffusion tensor imaging (DTI). In this study, 30 PD patients with resting tremor (PDWR), 26 PD patients without resting tremor (PDNR), and 30 healthy controls (HCs) from the Parkinson's Progression Markers Initiative (PPMI) cohort were included. Tract-based spatial statistics (TBSS) and region of interest-based analyses were conducted to determine white matter difference. Correlation analysis between DTI measures and clinical characteristics was also performed. In the whole brain, TBSS and region of interest-based analyses identified higher fractional anisotropy (FA) value, lower mean diffusivity (MD) value, and lower radial diffusivity (RD) in multiple fibers. In the cerebellum, TBSS analysis revealed significantly higher FA value, decreased RD value as well as MD value in multiple cerebellar tracts including the inferior cerebellar peduncle (ICP) and middle cerebellar peduncle (MCP) when comparing the PDWR with HC, and higher FA value in the MCP when compared with PDNR. We identified better white matter integrity in the cerebrum and cerebellum in PDWR indicating a potential association between the cerebral and cerebellar white matter and resting tremor in PD.

How should we be using biomarkers in trials of disease modification in Parkinson's disease?

The recent validation of the α-synuclein seed amplification assay as a biomarker with high sensitivity and specificity for the diagnosis of Parkinson's disease has formed the backbone for a proposed staging system for incorporation in Parkinson's disease clinical studies and trials. The routine use of this biomarker should greatly aid in the accuracy of diagnosis during recruitment of Parkinson's disease patients into trials (as distinct from patients with non-Parkinson's disease parkinsonism or non-Parkinson's disease tremors). There remain, however, further challenges in the pursuit of biomarkers for clinical trials of disease modifying agents in Parkinson's disease, namely: optimizing the distinction between different α-synucleinopathies; the selection of subgroups most likely to benefit from a candidate disease modifying agent; a sensitive means of confirming target engagement; and the early prediction of longer-term clinical benefit. For example, levels of CSF proteins such as the lysosomal enzyme β-glucocerebrosidase may assist in prognostication or allow enrichment of appropriate patients into disease modifying trials of agents with this enzyme as the target; the presence of coexisting Alzheimer's disease-like pathology (detectable through CSF levels of amyloid-β42 and tau) can predict subsequent cognitive decline; imaging techniques such as free-water or neuromelanin MRI may objectively track decline in Parkinson's disease even in its later stages. The exploitation of additional biomarkers to the α-synuclein seed amplification assay will, therefore, greatly add to our ability to plan trials and assess the disease modifying properties of interventions. The choice of which biomarker(s) to use in the context of disease modifying clinical trials will depend on the intervention, the stage (at risk, premotor, motor, complex) of the population recruited and the aims of the trial. The progress already made lends hope that panels of fluid biomarkers in tandem with structural or functional imaging may provide sensitive and objective methods of confirming that an intervention is modifying a key pathophysiological process of Parkinson's disease. However, correlation with clinical progression does not necessarily equate to causation, and the ongoing validation of quantitative biomarkers will depend on insightful clinical-genetic-pathophysiological comparisons incorporating longitudinal biomarker changes from those at genetic risk with evidence of onset of the pathophysiology and those at each stage of manifest clinical Parkinson's disease.

Parkinsonian Tremor Detection with Compact Convolutional Transformer from Bispectrum Representation of tri-Axial Accelerometer Signals.

After the breakthroughs of Transformer networks in Natural Language Processing (NLP) tasks, they have led to exciting progress in visual tasks as well. Nonetheless, there has been a parallel growth in the number of parameters and the amount of training data, which led to the conclusion that Transformers are not suited for small datasets. This paper is the first to convey the feasibility of Compact Convolutional Transformers (CCT) for the prediction of Parkinsonian postural tremor based on the Bispectrum (BS) representation of IMU accelerometer time series. The dataset includes tri-axial accelerometer signals collected unobtrusively in-the-wild while subjects are on a phone call, and labelled by neurologists and signal processing experts. The BS is a noise-immune, higher-order representation that reflects a signal's deviation from Gaussianity and measures quadratic phase coupling. We performed comparative classification experiments using the CCT, pre-trained CNNs such as VGG-16 and ResNet-50, and the conventional Vision Transformer (ViT). Our model achieves competitive prediction accuracy and F1 score of 96% with only 1.016 M trainable parameters, compared to the ViT with 21.659 M trainable parameters, in a five-fold cross-validation scheme. Our model also outperforms pre-trained CNNs such as VGG-16 and ResNet-50. Furthermore, we show that the performance gains are maintained when training on a larger dataset of BS images. Our effort here is motivated by the hypothesis that data-efficient transformers outperform transfer learning using pre-trained CNNs, paving the way for promising deep learning architecture for small-scale, novel and noisy medical imaging datasets.Clinical relevance- Novel deep learning model for unobtrusive prediction of Parkinsonian Postural Tremor from Bispectrum image representation of tri-axial accelerometer signals collected in-the-wild.

Amantadine for Refractory Tremor in Parkinson Disease and Other Indications: A Chart Review With Long-Term Follow-up.

The aim of this study was to determine how amantadine was used in a movement disorders clinic and how effective it was. A chart review over a 2-month period in 2022 of all patients in a movement disorders clinic who had ever taken amantadine was undertaken. One hundred six charts were included. Amantadine was initiated primarily for tremor and secondly for l -dopa-induced dyskinesias (LIDs). Sixty-two percent of tremor patients improved and tolerated amantadine; 74% of those with LID improved and tolerated the drug. Hallucinations occurred in 23%. Initiating amantadine as a syrup allowed a more conservative titration than other formulations, which is attractive given the high percentage of hallucinations that may occur. Patients who tolerated drug initiation were generally kept on the drug for many years. Amantadine should be considered as adjunctive therapy in Parkinson disease patients with refractory tremor as well as for LIDs.

Leveraging Unlabelled Data in Multiple-Instance Learning Problems for Improved Detection of Parkinsonian Tremor in Free-Living Conditions.

Data-driven approaches for remote detection of Parkinson's Disease and its motor symptoms have proliferated in recent years, owing to the potential clinical benefits of early diagnosis. The holy grail of such approaches is the free-living scenario, in which data are collected continuously and unobtrusively during every day life. However, obtaining fine-grained ground-truth and remaining unobtrusive is a contradiction and therefore, the problem is usually addressed via multiple-instance learning. Yet for large scale studies, obtaining even the necessary coarse ground-truth is not trivial, as a complete neurological evaluation is required. In contrast, large scale collection of data without any ground-truth is much easier. Nevertheless, utilizing unlabelled data in a multiple-instance setting is not straightforward, as the topic has received very little research attention. Here we try to fill this gap by introducing a new method for combining semi-supervised with multiple-instance learning. Our approach builds on the Virtual Adversarial Training principle, a state-of-the-art approach for regular semi-supervised learning, which we adapt and modify appropriately for the multiple-instance setting. We first establish the validity of the proposed approach through proof-of-concept experiments on synthetic problems generated from two well-known benchmark datasets. We then move on to the actual task of detecting PD tremor from hand acceleration signals collected in-the-wild, but in the presence of additional completely unlabelled data. We show that by leveraging the unlabelled data of 454 subjects we can achieve large performance gains (up to 9% increase in F1-score) in per-subject tremor detection for a cohort of 45 subjects with known tremor ground-truth. In doing so, we confirm the validity of our approach on a real-world problem where the need for semi-supervised and multiple-instance learning arises naturally.

Integrative Brain States Facilitate the Expression of Parkinson's Tremor.

Parkinson's disease (PD) rest tremor emerges from pathological activity in the basal ganglia and cerebello-thalamo-cortical circuits. A well-known clinical feature is the waxing and waning of PD tremor amplitude, but the mechanisms that drive this variability are unclear. Previous work has shown that arousal amplifies PD tremor by increasing between-network connectivity. Furthermore, brain states in PD are biased toward integration rather than segregation, a pattern that is also associated with increased arousal. The aim was to test the hypothesis that fluctuations in integrative brain states and/or arousal drive spontaneous fluctuations in PD rest tremor. We compared the temporal relationship between cerebral integration, the ascending arousal system, and tremor, both during cognitive load and in the resting state. In 40 tremor-dominant PD patients, we performed functional magnetic resonance imaging using concurrent tremor recordings and proxy measures of the ascending arousal system (pupil diameter, heart rate). We calculated whole-brain dynamic functional connectivity and used graph theory to determine a scan-by-scan measure of cerebral integration, which we related to the onset of tremor episodes. Fluctuations in cerebral integration were time locked to spontaneous changes in tremor amplitude: cerebral integration increased 13 seconds before tremor onset and predicted the amplitude of subsequent increases in tremor amplitude. During but not before tremor episodes, pupil diameter and heart rate increased and correlated with tremor amplitude. Integrative brain states are an important cerebral environment in which tremor-related activity emerges, which is then amplified by the ascending arousal system. New treatments focused on attenuating enhanced cerebral integration in PD may reduce tremor. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Distal Upper Limb Tremor during Walking in Parkinson's Disease.

Distal upper limb tremor during walking (TW) is frequently observed in Parkinson's disease (PD) but its clinical features are unknown. To characterize the occurrence and the clinical features of TW in comparison to the other types of tremors in PD. Fifty-one PD patients with rest tremor were evaluated off- and on-treatment. Occurrence, body distribution, severity and latency of TW and of other tremor types were assessed. TW was present in 78% of the PD patients examined. TW body distribution and severity were similar to those of rest and re-emergent tremor but different from the postural tremor presented by the same patients. TW latency, observed in 85% of patients, was on average 5.8 s. Dopaminergic treatment significantly improved TW, rest, and re-emergent tremor severity but left TW latency unaffected. TW is a frequent motor sign in PD and is likely a clinical variant of rest tremor.

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.

Tremor supression following treatment with MRgFUS: skull density ratio consistency and degree of posterior dentatorubrothalamic tract lesioning predicts long-term clinical outcomes in essential tremor.

Magnetic resonance-guided focussed ultrasound (MRgFUS) is an incisionless ablative procedure, widely used for treatment of Parkinsonian and Essential Tremor (ET). Enhanced understanding of the patient- and treatment-specific factors that influence sustained long-term tremor suppression could help clinicians achieve superior outcomes via improved patient screening and treatment strategy. We retrospectively analysed data from 31 subjects with ET, treated with MRgFUS at a single centre. Tremor severity was assessed with parts A, B and C of the Clinical Rating Scale for Tremor (CRST) as well as the combined CRST. Tremor in the dominant and non-dominant hand was assessed with Hand Tremor Scores (HTS), derived from the CRST. Pre- and post-treatment imaging data were analysed to determine ablation volume overlap with automated thalamic segmentations, and the dentatorubrothalamic tract (DRTT) and compared with percentage change in CRST and HTS following treatment. Tremor symptoms were significantly reduced following treatment. Combined pre-treatment CRST (mean: 60.7 ± 17.3) and HTS (mean: 19.2 ± 5.7) improved by an average of 45.5 and 62.6%, respectively. Percentage change in CRST was found to be significantly negatively associated with age (β = -0.375, p = 0.015), and SDR standard deviation (SDRSD; β = -0.324, p = 0.006), and positively associated with ablation overlap with the posterior DRTT (β = 0.535, p < 0.001). Percentage HTS improvement in the dominant hand decreased significantly with older age (β = -0.576, p < 0.01). Our results suggest that increased lesioning of the posterior region of the DRTT could result in greater improvements in combined CRST and non-dominant hand HTS, and that subjects with lower SDR standard deviation tended to experience greater improvement in combined CRST.

Gender disparities in deep brain stimulation surgery for Parkinson disease and essential tremor

BackgroundWomen with Parkinson’s Disease (PD) receive Deep Brain Stimulation (DBS) less often than men. ObjectiveTo determine gender differences in the use of DBS for PD and essential tremor (ET) in the United States and at a single academic center. MethodsThe Nationwide Readmissions Database (NRD) was used to identify patients with PD and ET who underwent DBS from 2016 to 2017. The primary outcome was a comparison of the proportions of women and men who underwent DBS using chi-square tests. Locally, we identified patients with PD and ET referred for DBS from 2011 to 2020. The primary outcomes included a comparison of the proportions of women and men who were referred, completed the evaluation, were approved for surgery, and underwent DBS using Fisher’s exact tests. ResultsFrom 2016–2017, 6952 patients with PD (30.5% women) and 3000 patients with ET (42.6% women) underwent DBS in the United States. At a single academic center, 428 patients with PD (30.6% women) and 126 patients with ET (34% women) were referred for DBS, which was significantly different than the proportion of women with PD and ET in the neurology clinic population (p = 0.001 and p < 0.001, respectively). In both groups, women and men were equally likely to complete the evaluation and be approved for surgery; however, women with ET were more likely to decline surgery (35% vs 13%, p = 0.05). ConclusionWomen with PD and ET were less likely to be referred for DBS evaluation, and women with ET were more likely to decline surgery once approved.

Vision-based estimation of MDS-UPDRS scores for quantifying Parkinson's disease tremor severity.

Parkinson's disease (PD) is a common neurodegenerative movement disorder among older individuals. As one of the typical symptoms of PD, tremor is a critical reference in the PD assessment. A widely accepted clinical approach to assessing tremors in PD is based on part III of the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS). However, expert assessment of tremor is a time-consuming and laborious process that poses considerable challenges to the medical evaluation of PD. In this paper, we proposed a novel model, Global Temporal-difference Shift Network (GTSN), to estimate the MDS-UPDRS score of PD tremors based on video. The PD tremor videos were scored according to the majority vote of multiple raters. We used Eulerian Video Magnification (EVM) pre-processing to enhance the representations of subtle PD tremors in the videos. To make the model better focus on the tremors in the video, we proposed a special temporal difference module, which stacks the current optical flow to the result of inter-frame difference. The prediction scores were obtained from the Residual Networks (ResNet) embedded with a novel module, the Global Shift Module (GSM), which allowed the features of the current segment to include the global segment features. We carried out independent experiments using PD tremor videos of different body parts based on the scoring content of the MDS-UPDRS. On a fairly large dataset, our method achieved an accuracy of 90.6% for hands with rest tremors, 85.9% for tremors in the leg, and 89.0% for the jaw. An accuracy of 84.9% was obtained for postural tremors. Our study demonstrated the effectiveness of computer-assisted assessment for PD tremors based on video analysis. The latest version of the code is available at https://github.com/199507284711/PD-GTSN.

153 Utilizing a 32-Channel System for Treatment of Complex Movement Disorders: Initial Case Series

INTRODUCTION: Complex, mixed movement disorders affecting multiple pathways (e.g., Holme’s Tremor (HT) or comorbid essential tremor (ET) with dystonia, among others) represent significant challenges for surgical treatment. These disease states are likely the result of combined or complex network pathologies, requiring multi-nodal targeting for DBS. METHODS: Multiple simultaneous deep targets were implanted using four 8-contact, directional leads placed through 2 burr-holes, which were connected to a 32-channel pulse generator. Targets were chosen based on disorders and comorbidities. RESULTS: Seven complex movement disorder patients were operated on at Stanford University using the approach described above. All seven patients in the series reported significant improvement in symptoms, and four patients also had objective metrics recorded demonstrating significant improvements. In these four patients, patient A presented with DBS-refractory Parkinsonian tremor and showed additional 17% reduction in UPDRS after addition of a third lead from an existing burr hole, utilizing the 32-channel system. Similarly patient C with HT and patients D and E with ET/dystonia all demonstrated significant improvement in TRS (p &lt; 0.01) and dystonic symptoms after bilateral dual targeting of VIM and GPi through two burr-holes. Programming utilized tailored fractionation and stimulation parameters to achieve optimal results. CONCLUSIONS: We present the largest initial case series demonstrating the feasibility of a 32-channel multi-target DBS strategy for treating complex movement disorders. This approach warrants further investigation for treating complex, multi-circuit neuropsychiatric disorders.

Top-down control of human motor thalamic neuronal activity during the auditory oddball task

The neurophysiology of selective attention in visual and auditory systems has been studied in animal models but not with single unit recordings in human. Here, we recorded neuronal activity in the ventral intermediate nucleus as well as the ventral oral anterior, and posterior nuclei of the motor thalamus in 25 patients with parkinsonian (n = 6) and non-parkinsonian tremors (n = 19) prior to insertion of deep brain stimulation electrodes while they performed an auditory oddball task. In this task, patients were requested to attend and count the randomly occurring odd or “deviant” tones, ignore the frequent standard tones and report the number of deviant tones at trial completion. The neuronal firing rate decreased compared to baseline during the oddball task. Inhibition was specific to auditory attention as incorrect counting or wrist flicking to the deviant tones did not produce such inhibition. Local field potential analysis showed beta (13–35 Hz) desynchronization in response to deviant tones. Parkinson’s disease patients off medications had more beta power than the essential tremor group but less neuronal modulation of beta power to the attended tones, suggesting that dopamine modulates thalamic beta oscillations for selective attention. The current study demonstrated that ascending information to the motor thalamus can be suppressed during auditory attending tasks, providing indirect evidence for the searchlight hypothesis in humans. These results taken together implicate the ventral intermediate nucleus in non-motor cognitive functions, which has implications for the brain circuitry for attention and the pathophysiology of Parkinson’s disease.

A Pilot Study of Ex Vivo Human Prefrontal RNA Transcriptomics in Parkinson's Disease.

Parkinson's disease (PD) can dramatically change cortical neurophysiology. The molecular basis for PD-related cortical changes is unclear because gene expression data are usually derived from postmortem tissue collected at the end of a complex disease and they profoundly change in the minutes after death. Here, we studied cortical changes in tissue from the prefrontal cortex of living PD patients undergoing deep-brain stimulation implantation surgery. We examined 780 genes using the NanoString nCounter platform and found that 40 genes were differentially expressed between PD (n = 12) and essential tremor (ET; n = 9) patients. One of these 40 genes, STAT1, correlated with intraoperative 4-Hz rhythms and intraoperative performance of an oddball reaction-time task. Using a pre-designed custom panel of 780 targets, we compared these intraoperative data with those from a separate cohort of fresh-frozen tissue from the same frontal region in postmortem human PD donors (n = 6) and age-matched neurotypical controls (n = 6). This cohort revealed 279 differentially expressed genes. Fifteen of the 40 intraoperative PD-specific genes overlapped with postmortem PD-specific genes, including CALB2 and FOXP2. Transcriptomic analyses identified pathway changes in PD that had not been previously observed in postmortem cases. These molecular signatures of cortical function and dysfunction may help us better understand cognitive and neuropsychiatric aspects of PD.

Pharmacological Treatment of Tremor in Parkinson's Disease Revisited.

The pathophysiology of Parkinson's disease (PD) tremor remains incompletely understood and there is a lack of clinical trials specifically addressing its pharmacological treatment. Levodopa is the most efficacious drug for most patients and should be used as primary approach to control troublesome tremor. While the efficacy of oral dopamine agonists on PD tremor has been demonstrated in controlled trials, there is no evidence of greater antitremor efficacy compared to levodopa. The magnitude of the antitremor effect of anticholinergics is generally lower than that of levodopa. Due to their adverse effects, anticholinergics have a limited role in selected young and cognitively intact patients. Propranolol may improve resting and action tremor and may be considered as an adjunct in patients with insufficient tremor response to levodopa and this also applies to clozapine, despite its unfavorable adverse effect profile. Treating motor fluctuations with MAO-B and COMT inhibitors, dopamine agonists, amantadine, or on-demand treatments such as subcutaneous or sublingual apomorphine and inhaled levodopa as well as with continuous infusions of levodopa or apomorphine will improve off period tremor episodes. For patients with drug-refractory PD tremor despite levodopa optimization deep brain stimulation and focused ultrasound are first-line considerations. Surgery can also be highly effective for the treatment medication-refractory tremor in selected patients without motor fluctuations. The present review highlights the clinical essentials of parkinsonian tremor, critically examines available trial data on the effects of medication and surgical approaches and provides guidance for the choice of treatments to control PD tremor in clinical practice.