Bayesian Interpretation of Essential Tremor Plus

Essential tremor (ET) plus is a new tremor classification that was introduced in 2018 by a task force of the International Parkinson and Movement Disorder Society. Patients with ET plus meet the criteria for ET but have one or more additional systemic or neurologic signs of uncertain significance or relevance to tremor (“soft signs”). Soft signs are not sufficient to diagnose another tremor syndrome or movement disorder, and soft signs in ET plus are known to have poor interrater reliability and low diagnostic sensitivity and specificity. Therefore, the clinical significance of ET plus must be interpreted probabilistically when judging whether a patient is more likely to have ET or a combined tremor syndrome, such as dystonic tremor. Such a probabilistic interpretation is possible with Bayesian analysis. This review presents a Bayesian analysis of ET plus in patients suspected of having ET versus a dystonic tremor syndrome, which is the most common differential diagnosis in patients referred for ET. Bayesian analysis of soft signs provides an estimate of the probability that a patient with possible ET is more likely to have an alternative diagnosis. ET plus is a distinct tremor classification and should not be viewed as a subtype of ET. ET plus covers a more-comprehensive phenotyping of people with possible ET, and the clinical interpretation of ET plus is enhanced with Bayesian analysis of associated soft signs.     

特发性震颤的研究进展

特发性震颤（ET）的病因可能包括环境和遗传因素。血中哈尔碱和铅浓度的增高可能和ET发病有关。遗传具有异质性,目前已经发现有3个基因位点可能与其发病有关,GABA转运体1型（GABA transporter subtype1,GAT1）可能为另一个候选基因。除震颤外,ET患者还可有小脑体征、执行功能受损和痴呆等表现。目前有一些新的辅助检查手段帮助鉴别ET,尤其是与早期帕金森病震颤相鉴别。一些新的药物也被证实有效。     

Tremor during movement correlates well with disability in people with essential tremor

Essential tremor is the most common movement disorder, typically characterized by the presence of both postural and kinetic tremor of the hand. In recent studies, we described the effects of altering force and load conditions on tremor amplitude and power in people with essential tremor. In the same participants, we also measured tremor‐related functional disability. In this article we report on the current study on correlations of measures of tremor severity with those of tremor‐related functional disability. Twenty‐one participants with essential tremor had tremor measured in their more tremorous hand. Power spectral and amplitude measures of tremor were calculated for each of 16 conditions: force tremor at 4 submaximal force levels, postural tremor in unloaded and 3 submaximal load conditions, and kinetic tremor in unloaded and 3 submaximal load conditions for each of concentric and eccentric contractions of the wrist extensors. Participants were rated on the hand items of the Fahn‐Tolosa‐Marin rating scale and timed on the unilateral hand tasks of the Test Évaluant la Performance des Membres supérieurs des Personnes Âgées. The most consistently high and significant correlations were found between kinetic tremor measures and the hand task scores and tremor‐B scores (r = 0.548–0.780, P < .01). Postural tremor measures correlated with disability measures only in loaded conditions, most consistently with the hand task measures (r = 0.640–0.725, P < .01). Thus, measures of kinetic tremor and loaded postural tremor, but not unloaded postural tremor or force tremor, relate well to disability captured with dynamic tasks. © 2011 Movement Disorder Society     

磁共振测量特发性震颤和帕金森病患者基底节区核团体积的研究

目的：利用磁共振体积测量技术评价特发性震颤（ET）,帕金森病（PD）患者基底节区核团体积的变化及互相间的差异。方法：采用1．5T磁共振机测量9例ET患者、5例PD患者和8例年龄匹配正常人全脑体积、尾状核和壳核体积。比较各组之间感兴趣区体积的差异。结果：PD组双侧尾状核标化体积之和、双侧壳核标化体积之和较正常人缩小（P〈0．05）。ET组双侧尾状核标化体积,双侧壳核标化体积与正常对照组无差别。结论：PD患者存在尾状核和壳核体积的缩小,而ET患者无明显尾状核和壳核体积变化。     

The Role of the Cerebellum in Degenerative Ataxias and Essential Tremor: Insights From Noninvasive Modulation of Cerebellar Activity

Over the last three decades, measuring and modulating cerebellar activity and its connectivity with other brain regions has become an emerging research topic in clinical neuroscience. The most important connection is the cerebellothalamocortical pathway, which can be functionally interrogated using a paired-pulse transcranial magnetic stimulation paradigm. Cerebellar brain inhibition reflects the magnitude of suppression of motor cortex excitability after stimulating the contralateral cerebellar hemisphere and therefore represents a neurophysiological marker of the integrity of the efferent cerebellar tract. Observations that cerebellar noninvasive stimulation techniques enhanced performance of certain motor and cognitive tasks in healthy individuals have inspired attempts to modulate cerebellar activity and connectivity in patients with cerebellar diseases in order to achieve clinical benefit. We here comprehensively explore the therapeutic potential of these techniques in two movement disorders characterized by prominent cerebellar involvement, namely the degenerative ataxias and essential tremor. The article aims to illustrate the (patho)physiological insights obtained from these studies and how these translate into clinical practice, where possible by addressing the association with cerebellar brain inhibition. Finally, possible explanations for some discordant interstudy findings, shortcomings in our current understanding, and recommendations for future research will be provided. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.     

Distribution of tremor among the major degrees of freedom of the upper limb in subjects with Essential Tremor

ObjectiveAlthough Essential Tremor is one of the most common movement disorders, we do not currently know which muscles are most responsible for tremor. Determining this requires multiple steps, one of which is characterizing the distribution of tremor among the degrees of freedom (DOF) of the upper limb.MethodsUpper-limb motion was recorded while 22 subjects with ET performed postural and kinetic tasks involving a variety of limb configurations. We calculated the mean distribution of tremor among the seven DOF from the shoulder to the wrist, as well as the effect of limb configuration, repetition, and subject characteristics (sex, tremor onset, duration, and severity) on the distribution.ResultsOn average, kinetic tremor was greatest in forearm pronation-supination and wrist flexion–extension, intermediate in shoulder internal-external rotation and wrist radial-ulnar deviation and then shoulder flexion–extension and elbow flexion–extension, and least in shoulder abduction–adduction. The average distribution of postural tremor was similar except for forearm pronation-supination, which played a smaller role than in kinetic tremor. Limb configuration and subject characteristics did significantly affect tremor, but practically only in forearm pronation-supination and wrist flexion–extension. There were no significant differences between repetitions, indicating that the distribution was consistent over the duration of the experiment.ConclusionsThis paper presents a thorough characterization of tremor distribution from the shoulder to the wrist.SignificanceUnderstanding which DOF exhibit the most tremor may lead to more targeted peripheral tremor suppression.     

Improving the Accuracy of Scores to Predict Gastrostomy after Intracerebral Hemorrhage with Machine Learning

Background

Gastrostomy placement after intracerebral hemorrhage indicates the need for continued medical care and predicts patient dependence. Our objective was to determine the optimal machine learning technique to predict gastrostomy.

Parkinsonism and essential tremor in a family with pseudo-dominant inheritance of PARK2: an FP-CIT SPECT study.

We report a family with 5 affected individuals manifesting either essential tremor (ET), Parkinsonism, or both, consistent with pseudo-dominant inheritance of PARK2. Two homozygotes presented postural and kinetic tremor several years before the onset of Parkinsonism. Postural and kinetic tremor mimicking ET was the only feature in 1 homozygous and 2 heterozygous carriers of the mutation. Striatal dopamine transporter density was reduced in accordance with phenotype and number of mutated alleles. In 3 homozygotes and 1 heterozygote, a 2-year follow-up single photon emission computed tomography suggested no progression of nigrostriatal deficit.     

Prediction of Outcomes in Mini-Basketball Training Program for Preschool Children with Autism Using Machine Learning Models

In recent years evidence has emerged suggesting that Mini-basketball training program (MBTP) can be an effective intervention method to improve social communication (SC) impairments and restricted and repetitive behaviors (RRBs) in preschool children suffering from autism spectrum disorder (ASD). However, there is a considerable degree if interindividual variability concerning these social outcomes and thus not all preschool children with ASD profit from a MBTP intervention to the same extent. In order to make more accurate predictions which preschool children with ASD can benefit from an MBTP intervention or which preschool children with ASD need additional interventions to achieve behavioral improvements, further research is required. This study aimed to investigate which individual factors of preschool children with ASD can predict MBTP intervention outcomes concerning SC impairments and RRBs. Then, test the performance of machine learning models in predicting intervention outcomes based on these factors. Participants were 26 preschool children with ASD who enrolled in a quasi-experiment and received MBTP intervention. Baseline demographic variables (e.g., age, body, mass index [BMI]), indicators of physical fitness (e.g., handgrip strength, balance performance), performance in executive function, severity of ASD symptoms, level of SC impairments, and severity of RRBs were obtained to predict treatment outcomes after MBTP intervention. Machine learning models were established based on support vector machine algorithm were implemented. For comparison, we also employed multiple linear regression models in statistics. Our findings suggest that in preschool children with ASD symptomatic severity (r = 0.712, p < 0.001) and baseline SC impairments (r = 0.713, p < 0.001) are predictors for intervention outcomes of SC impairments. Furthermore, BMI (r = −0.430, p = 0.028), symptomatic severity (r = 0.656, p < 0.001), baseline SC impairments (r = 0.504, p = 0.009) and baseline RRBs (r = 0.647, p < 0.001) can predict intervention outcomes of RRBs. Statistical models predicted 59.6% of variance in post-treatment SC impairments (MSE = 0.455, RMSE = 0.675, R2 = 0.596) and 58.9% of variance in post-treatment RRBs (MSE = 0.464, RMSE = 0.681, R2 = 0.589). Machine learning models predicted 83% of variance in post-treatment SC impairments (MSE = 0.188, RMSE = 0.434, R2 = 0.83) and 85.9% of variance in post-treatment RRBs (MSE = 0.051, RMSE = 0.226, R2 = 0.859), which were better than statistical models. Our findings suggest that baseline characteristics such as symptomatic severity of ASD symptoms and SC impairments are important predictors determining MBTP intervention-induced improvements concerning SC impairments and RBBs. Furthermore, the current study revealed that machine learning models can successfully be applied to predict the MBTP intervention-related outcomes in preschool children with ASD, and performed better than statistical models. Our findings can help to inform which preschool children with ASD are most likely to benefit from an MBTP intervention, and they might provide a reference for the development of personalized intervention programs for preschool children with ASD.     

Heterogeneity and Classification of Recent Onset Psychosis and Depression: A Multimodal Machine Learning Approach

Diagnostic heterogeneity within and across psychotic and affective disorders challenges accurate treatment selection, particularly in the early stages. Delineation of shared and distinct illness features at the phenotypic and brain levels may inform the development of more precise differential diagnostic tools. We aimed to identify prototypes of depression and psychosis to investigate their heterogeneity, with common, comorbid transdiagnostic symptoms. Analyzing clinical/neurocognitive and grey matter volume (GMV) data from the PRONIA database, we generated prototypic models of recent-onset depression (ROD) vs. recent-onset psychosis (ROP) by training support-vector machines to separate patients with ROD from patients with ROP, who were selected for absent comorbid features (pure groups). Then, models were applied to patients with comorbidity, ie, ROP with depressive symptoms (ROP+D) and ROD participants with sub-threshold psychosis-like features (ROD+P), to measure their positions within the affective-psychotic continuum. All models were independently validated in a replication sample. Comorbid patients were positioned between pure groups, with ROP+D patients being more frequently classified as ROD compared to pure ROP patients (clinical/neurocognitive model: χ² = 14.874; P < .001; GMV model: χ² = 4.933; P = .026). ROD+P patient classification did not differ from ROD (clinical/neurocognitive model: χ² = 1.956; P = 0.162; GMV model: χ² = 0.005; P = .943). Clinical/neurocognitive and neuroanatomical models demonstrated separability of prototypic depression from psychosis. The shift of comorbid patients toward the depression prototype, observed at the clinical and biological levels, suggests that psychosis with affective comorbidity aligns more strongly to depressive rather than psychotic disease processes. Future studies should assess how these quantitative measures of comorbidity predict outcomes and individual responses to stratified therapeutic interventions.     

Quantification of ligand PET studies using a reference region with a displaceable fraction: application to occupancy studies with [11C]-DASB as an example

This paper aims to build novel methodology for the use of a reference region with specific binding for the quantification of brain studies with radioligands and positron emission tomography (PET). In particular: (1) we introduce a definition of binding potential BP_D=DVR−1 where DVR is the volume of distribution relative to a reference tissue that contains ligand in specifically bound form, (2) we validate a numerical methodology, rank-shaping regularization of exponential spectral analysis (RS-ESA), for the calculation of BP_D that can cope with a reference region with specific bound ligand, (3) we demonstrate the use of RS-ESA for the accurate estimation of drug occupancies with the use of correction factors to account for the specific binding in the reference. [¹¹C]-DASB with cerebellum as a reference was chosen as an example to validate the methodology. Two data sets were used; four normal subjects scanned after infusion of citalopram or placebo and further six test–retest data sets. In the drug occupancy study, the use of RS-ESA with cerebellar input plus corrections produced estimates of occupancy very close the ones obtained with plasma input. Test–retest results demonstrated a tight linear relationship between BP_D calculated either with plasma or with a reference input and high reproducibility.