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Background: The presence of frequent macro-square-wave jerks (SWJs) has been recently included in the diagnostic criteria for progressive supranuclear palsy (PSP). The aim of the current video-oculographic study was to systematically assess the presence and features of SWJs during a brief fixation task in PSP, in comparison with Parkinson's disease (PD) patients and healthy controls (HC)., Methods: Thirty-eight PSP patients, 55 PD patients and 40 HC were enrolled in the study. All patients underwent a video-oculographic (VOG) examination including a 5-s fixation task, and the number, duration and amplitude of SWJs were recorded. The diagnostic performance of several SWJs parameters were then compared in distinguishing PSP from PD patients and controls., Results: PSP patients showed a higher number and amplitude of SWJs compared to PD patients and controls. At least two SWJs within the 5-s fixation task were observed in 81.6% of PSP patients, 52.7% of PD patients and 25% of HC. The SWJs amplitude was the parameter showing the highest performances in distinguishing PSP from PD (AUC: 0.78) and HC (AUC: 0.88), outperforming the SWJ number and duration. The SWJ amplitude was larger in PSP-Richardson's syndrome than in PSP-Parkinsonism patients, while no difference was found between PSP patients with different degrees of vertical ocular motor dysfunction., Conclusions: This video-oculographic study provides robust evidence of larger SWJs number and amplitude in PSP than in PD patients, with some potential for differential diagnosis, supporting the inclusion of this ocular sign in PSP criteria., (© 2024. The Author(s).)

Introduction: Distinguishing tremor-dominant Parkinson's disease (tPD) from essential tremor with rest tremor (rET) can be challenging and often requires dopamine imaging. This study aimed to differentiate between these two diseases through a machine learning (ML) approach based on rest tremor (RT) electrophysiological features and structural MRI data., Methods: We enrolled 72 patients including 40 tPD patients and 32 rET patients, and 45 control subjects (HC). RT electrophysiological features (frequency, amplitude, and phase) were calculated using surface electromyography (sEMG). Several MRI morphometric variables (cortical thickness, surface area, cortical/subcortical volumes, roughness, and mean curvature) were extracted using Freesurfer. ML models based on a tree-based classification algorithm termed XGBoost using MRI and/or electrophysiological data were tested in distinguishing tPD from rET patients., Results: Both structural MRI and sEMG data showed acceptable performance in distinguishing the two patient groups. Models based on electrophysiological data performed slightly better than those based on MRI data only (mean AUC: 0.92 and 0.87, respectively; p = 0.0071). The top-performing model used a combination of sEMG features (amplitude and phase) and MRI data (cortical volumes, surface area, and mean curvature), reaching AUC: 0.97 ± 0.03 and outperforming models using separately either MRI ( p = 0.0001) or EMG data ( p = 0.0231). In the best model, the most important feature was the RT phase., Conclusion: Machine learning models combining electrophysiological and MRI data showed great potential in distinguishing between tPD and rET patients and may serve as biomarkers to support clinicians in the differential diagnosis of rest tremor syndromes in the absence of expensive and invasive diagnostic procedures such as dopamine imaging., Competing Interests: BV was employed by Biotecnomed S.c.a.r.l. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Aracri, Quattrone, Bianco, Sarica, De Maria, Calomino, Crasà, Nisticò, Buonocore, Vescio, Vaccaro and Quattrone.)

Objective: To investigate the performance of structural MRI cortical and subcortical morphometric data combined with blink-reflex recovery cycle (BRrc) values using machine learning (ML) models in distinguishing between essential tremor (ET) with resting tremor (rET) and classic ET., Methods: We enrolled 47 ET, 43 rET patients and 45 healthy controls (HC). All participants underwent brain 3 T-MRI and BRrc examination at different interstimulus intervals (ISIs, 100-300 msec). MRI data (cortical thickness, volumes, surface area, roughness, mean curvature and subcortical volumes) were extracted using Freesurfer on T1-weighted images. We employed two decision tree-based ML classification algorithms (eXtreme Gradient Boosting [XGBoost] and Random Forest) combining MRI data and BRrc values to differentiate between rET and ET patients., Results: ML models based exclusively on MRI features reached acceptable performance (AUC: 0.85-0.86) in differentiating rET from ET patients and from HC. Similar performances were obtained by ML models based on BRrc data (AUC: 0.81-0.82 in rET vs. ET and AUC: 0.88-0.89 in rET vs. HC). ML models combining imaging data (cortical thickness, surface, roughness, and mean curvature) together with BRrc values showed the highest classification performance in distinguishing between rET and ET patients, reaching AUC of 0.94 ± 0.05. The improvement in classification performances when BRrc data were added to imaging features was confirmed by both ML algorithms., Conclusion: This study highlights the usefulness of adding a simple electrophysiological assessment such as BRrc to MRI cortical morphometric features for accurately distinguishing rET from ET patients, paving the way for a better classification of these ET syndromes., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Calomino, Quattrone, Bianco, Nisticò, Buonocore, Crasà, Vaccaro, Sarica and Quattrone.)

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.

Introduction: There is some debate on the relationship between essential tremor with rest tremor (rET) and the classic ET syndrome, and only few MRI studies compared ET and rET patients. This study aimed to explore structural cortical differences between ET and rET, to improve the knowledge of these tremor syndromes., Methods: Thirty-three ET patients, 30 rET patients and 45 control subjects (HC) were enrolled. Several MR morphometric variables (thickness, surface area, volume, roughness, mean curvature) of brain cortical regions were extracted using Freesurfer on T1-weighted images and compared among groups. The performance of a machine learning approach (XGBoost) using the extracted morphometric features was tested in discriminating between ET and rET patients., Results: rET patients showed increased roughness and mean curvature in some fronto-temporal areas compared with HC and ET, and these metrics significantly correlated with cognitive scores. Cortical volume in the left pars opercularis was also lower in rET than in ET patients. No differences were found between ET and HC. XGBoost discriminated between rET and ET with mean AUC of 0.86 ± 0.11 in cross-validation analysis, using a model based on cortical volume. Cortical volume in the left pars opercularis was the most informative feature for classification between the two ET groups., Conclusion: Our study demonstrated higher cortical involvement in fronto-temporal areas in rET than in ET patients, which may be linked to the cognitive status. A machine learning approach based on MR volumetric data demonstrated that these two ET subtypes can be distinguished using structural cortical features., (© 2023. The Author(s).)

Background: Imaging studies investigating cerebellar gray matter (GM) in essential tremor (ET) showed conflicting results. Moreover, no large study explored the cerebellum in ET patients with resting tremor (rET), a syndrome showing enhanced blink reflex recovery cycle (BRrc)., Objective: To investigate cerebellar GM in ET and rET patients using voxel-based morphometry (VBM) analysis., Methods: Seventy ET patients with or without resting tremor and 39 healthy controls were enrolled. All subjects underwent brain 3 T-MRI and BRrc recording. We compared the cerebellar GM volumes between ET (n = 40) and rET (n = 30) patients and controls through a VBM analysis. Moreover, we investigated possible correlations between cerebellar GM volume and R2 component of BRrc., Results: rET and ET patients had similar disease duration. All rET patients and none of ET patients had enhanced BRrc. No differences in the cerebellar volume were found when ET and rET patients were compared to each other or with controls. By considering together the two tremor syndromes in a large patient group, the VBM analysis showed bilateral clusters of reduced GM volumes in Crus II in comparison with controls. The linear regression analysis in rET patients revealed a cluster in the left Crus II where the decrease in GM volume correlated with the R2BRrc increase., Conclusion: Our study suggests that ET and rET are different tremor syndromes with similar mild cerebellar gray matter involvement. In rET patients, the left Crus II may play a role in modulating the brainstem excitability, encouraging further studies on the role of cerebellum in these patients., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany.)

Background: Rest tremor (RT) can be observed in several positions (seated, standing, lying down) but it is unknown whether the tremor features may vary across them. This study aimed to compare the RT electrophysiological features across different positions in tremor-dominant Parkinson's disease (PD) and essential tremor plus (ET with RT, rET)., Methods: We consecutively enrolled 90 tremor-dominant PD and 24 rET patients. The RT presence was evaluated in three positions: with the patient seated, the arm flexed at 90°, the forearm supported against gravity, and the hand hanging down from the chair armrest (hand-hanging position), in lying down supine and in standing position. RT electrophysiological features (amplitude, frequency, burst duration, pattern) were compared between the two patient groups and across the different positions., Results: All PD and rET patients showed RT in hand-hanging position. Supine and standing RT were significantly more common in PD (67.8% and 75.6%, respectively) than in rET patients (37.5% and 45.8%, respectively). RT amplitude, frequency and pattern were significantly different between groups in hand-hanging position whereas only pattern was significantly different between PD and rET in both standing and supine positions. In each patient group, all RT electrophysiological features did not significantly vary across different recording positions (p > 0.05)., Discussion: In our study, PD and rET showed RT in hand-hanging, supine, and standing positions. RT pattern was the only electrophysiological feature significantly different between PD and rET patients in all these positions, enabling clinicians to perform the RT analysis for diagnostic purposes in different tremor positions., (© 2022. Fondazione Società Italiana di Neurologia.)

Introduction: Progressive supranuclear palsy (PSP) patients show reduced amplitude and velocity of vertical saccades, but saccadic abnormalities have also been reported in Parkinson's disease (PD). We investigated amplitude and velocity of vertical saccades in PSP and PD patients, to establish the best video-oculographic (VOG) parameters for PSP diagnosis., Methods: Fifty-one PSP patients, 113 PD patients and 40 controls were enrolled. The diagnosis was performed on a clinico-radiological basis (MR Parkinsonism index [MRPI] and MRPI 2.0). We used VOG to assess the diagnostic performances of saccadic amplitude, peak velocity, and their product (AxV) in upward or downward direction and in vertical gaze (upward and downward averaged) in distinguishing PSP from PD patients. The vestibulo-ocular reflex, necessary to establish the supranuclear nature of ocular dysfunction, was evaluated clinically., Results: PSP patients showed significantly reduced amplitude and peak velocity of ocular saccades in upward and downward directions compared to PD and healthy subjects. In PD patients, upward gaze amplitude was lower than in controls. In vertical gaze, the peak velocity showed 99.1% specificity and 54.7% sensitivity for PSP classification. The AxV product showed high specificity (94.7%) and sensitivity (84.3%) and yielded higher accuracy (91.5%) than velocity and amplitude used alone in distinguishing PSP from PD., Conclusion: Our study demonstrates that the peak velocity of vertical saccades was a very low sensitive parameter and cannot be used alone for PSP diagnosis. A new index combining amplitude and peak velocity in vertical gaze seems the most suitable video-oculographic biomarker for differentiating PSP from PD and controls., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Background: The R2 component of blink reflex recovery cycle (R2BRrc) is a simple neurophysiological tool to detect the brainstem hyperexcitability commonly occurring in several neurological diseases such as Parkinson's disease and atypical parkinsonisms. In our study, we investigated for the first time the usefulness of R2BRrc to assess brainstem excitability in patients with idiopathic Normal Pressure Hydrocephalus (iNPH) in comparison with healthy subjects., Methods: Eighteen iNPH patients and 25 age-matched control subjects were enrolled. R2BRrc was bilaterally evaluated at interstimulus intervals (ISIs) of 100, 150, 200, 300, 400, 500 and 750 ms in all participants. We investigated the diagnostic performance of R2BRrc in differentiating iNPH patients from control subjects using ROC analysis. Midbrain area and Magnetic Resonance Hydrocephalic Index (MRHI), an MRI biomarker for the diagnosis of iNPH, were measured on T1-weighted MR images, and correlations between R2BRrc values and MRI measurements were investigated., Results: Fourteen (78%) of 18 iNPH patients showed an enhanced R2BRrc at ISIs 100-150-200 ms, while no control subjects had abnormal R2BRrc. The mean amplitude of bilateral R2BRrc at the shortest ISIs (100-150-200 ms) showed high accuracy in differentiating iNPH patients from controls (AUC = 0.89). R2BRrc values significantly correlated with midbrain area and MRHI values., Conclusions: This study represents the first evidence of brainstem hyperexcitability in iNPH patients. Given its low cost and wide availability, R2BRrc could be a useful tool for selecting elderly subjects with mild gait and urinary dysfunction who should undergo an extensive diagnostic workup for the diagnosis of NPH., (© 2021. Springer-Verlag GmbH Germany, part of Springer Nature.)

Tremor is an impairing symptom associated with several neurological diseases. Some of such diseases are neurodegenerative, and tremor characterization may be of help in differential diagnosis. To date, electromyography (EMG) is the gold standard for the analysis and diagnosis of tremors. In the last decade, however, several studies have been conducted for the validation of different techniques and new, non-invasive, portable, or even wearable devices have been recently proposed as complementary tools to EMG for a better characterization of tremors. Such devices have proven to be useful for monitoring the efficacy of therapies or even aiding in differential diagnosis. The aim of this review is to present systematically such new solutions, trying to highlight their potentialities and limitations, with a hint to future developments., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Vescio, Quattrone, Nisticò, Crasà and Quattrone.)

Involuntary tremor at rest is observed in patients with Parkinson's disease (PD) or essential tremor (ET). Electromyography (EMG) studies have shown that phase displacement between antagonistic muscles at prevalent tremor frequency can accurately differentiate resting tremor in PD from that detected in ET. Currently, phase evaluation is qualitative in most cases. The aim of this study is to develop and validate a new mobile tool for the automated and quantitative characterization of phase displacement (resting tremor pattern) in ambulatory clinical settings. A new low-cost, wearable mobile device, called µEMG, is described, based on low-end instrumentation amplifiers and simple digital signal processing (DSP) capabilities. Measurements of resting tremor characteristics from this new device were compared with standard EMG. A good level of agreement was found in a sample of 21 subjects (14 PD patients with alternating resting tremor pattern and 7 ET patients with synchronous resting tremor pattern). Our results demonstrate that tremor analysis using µEMG is easy to perform and it can be used in routine clinical practice for the automated quantification of resting tremor patterns. Moreover, the measurement process is handy and operator-independent.

Introduction: Apomorphine is a dopamine agonist used in Parkinson's disease (PD), which matches levodopa in terms of the magnitude of effect on the cardinal motor features, such as tremor and bradykinesia. The beneficial effect of this treatment on PD patients with tremor-dominant has widely been demonstrated, although the underlying neural correlates are unknown. We sought to examine the effects of apomorphine on topological characteristics of resting-state functional connectivity networks in tremor-dominant PD (tdPD) patients., Methods: Sixteen tdPD patients were examined using a combined electromyography-functional magnetic resonance imaging approach. Patients were scanned twice following either placebo (subcutaneous injection of 1 mL saline solution) or 1 mg of apomorphine injection. Graph analysis methods were employed to investigate the modular organization of functional connectivity networks before and after drug treatment., Results: After injection of apomorphine, evident reduction of tremor symptoms was mirrored by a significant increase in overall connectivity strength and reorganization of the modular structure of the basal ganglia and of the fronto-striatal module. Moreover, we found an increase in the centrality of motor and premotor regions. No differences were found between pre- and post-placebo sessions., Conclusion: These results provide new evidence about the effects of apomorphine at a large-scale neural network level showing that drug treatment modifies the brain functional organization of tdPD, increasing the overall resting-state functional connectivity strength, the segregation of striato-frontal regions and the integrative role of motor areas., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

According to embodied cognition, processing language with motor content involves a simulation of this content by the brain motor system. Patients with brain lesions involving the motor system are characterized by deficits in action verbs processing in the absence of dementia. We sought to assess whether action verbs interfere with the motor behavior of patients with Parkinson's disease (PD) having tremor dominant symptoms. PD tremor is considered to result from dysfunction of cortical-subcortical motor circuits driven by dopamine depletion. In addition, PD tremor is reduced during active movement execution. Therefore, likewise movement execution, the motor simulation of bodily actions predicted by the embodiment may show to be effective in modifying tremor by interfering with a dysfunctional motor system. Here, we asked to simply read and repeat words expressing a hand-related bodily action. Abstract verbs served as control. Changes in tremor kinematics were evaluated using a monoaxial accelerometer. Seventeen PD patients with rest tremor of the upper limbs were enrolled. Tremor amplitude was significantly smaller when reading action verbs as compared to abstract verbs. We provide empirical evidence supporting the embodied cognition theory by showing that circuits mediating tremor of PD patients are distinctively affected by processing action language., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Introduction: The aim of our study was to investigate the effect of apomorphine and placebo on resting tremor in tremor-dominant Parkinson's disease (tPD) patients., Methods: Fifteen tPD patients were enrolled. Each patient underwent two treatments on two consecutive days: on day one the patients received a subcutaneous injection of placebo, while on day two they received apomorphine. On each day, the patients underwent three electrophysiological recording sessions: T0, T1, and T2: before, 30 min, and 60 min after the treatment respectively. Electrophysiological changes in tremor amplitude were evaluated using a triaxial accelerometer., Results: Placebo was effective in improving resting tremor in all tPD patients (p = 0.009) at T1, but not at T2. Eight out of 15 tPD patients (53.3%) responded to placebo with an at least 70% reduction in tremor amplitude compared to the basal condition (responders). By contrast, seven out of 15 tPD patients (46.7%) did not show any variation in tremor amplitude after placebo administration (non-responders). Apomorphine induced a marked reduction in tremor amplitude at 30 min and 60 min in all investigated tPD patients. Of note, the decrease in tremor amplitude in placebo responders was similar to that achieved with dopaminergic stimulation induced by apomorphine., Conclusions: Our study demonstrates that placebo was very effective in reducing resting tremor in about half of patients with tPD. The decrease in tremor amplitude in placebo responders was similar to that induced by apomorphine. The cerebral mechanisms underlying the placebo effect on resting tremor need further investigations., (Copyright © 2018 Elsevier Ltd. All rights reserved.)