Quantitative Separation of Tremor and Ataxia in Essential Tremor

Motor Output Variability in Movement Disorders: Insights From Essential Tremor

Findings on individuals with essential tremor suggest that tremor (within-trial movement unsteadiness) and inconsistency (trial-to-trial movement variance) stem from distinct pathologies and affect function uniquely. Nonetheless, the intricacies of inconsistency in movement disorders remain largely unexplored, as exemplified in ataxia where inconsistency below healthy levels is associated with greater pathology. We advocate for clinical assessments that quantify both tremor and inconsistency.

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.

Cerebellar Excitability Regulates Physical Fatigue Perception

Fatigue is the subjective sensation of weariness, increased sense of effort, or exhaustion and is pervasive in neurologic illnesses. Despite its prevalence, we have a limited understanding of the neurophysiological mechanisms underlying fatigue. The cerebellum, known for its role in motor control and learning, is also involved in perceptual processes. However, the role of the cerebellum in fatigue remains largely unexplored. We performed two experiments to examine whether cerebellar excitability is affected after a fatiguing task and its association with fatigue. Using a crossover design, we assessed cerebellar inhibition (CBI) and perception of fatigue in humans before and after "fatigue" and "control" tasks. Thirty-three participants (16 males, 17 females) performed five isometric pinch trials with their thumb and index finger at 80% maximum voluntary capacity (MVC) until failure (force <40% MVC; fatigue) or at 5% MVC for 30 s (control). We found that reduced CBI after the fatigue task correlated with a milder perception of fatigue. In a follow-up experiment, we investigated the behavioral consequences of reduced CBI after fatigue. We measured CBI, perception of fatigue, and performance during a ballistic goal-directed task before and after the same fatigue and control tasks. We replicated the observation that reduced CBI after the fatigue task correlated with a milder perception of fatigue and found that greater endpoint variability after the fatigue task correlated with reduced CBI. The proportional relation between cerebellar excitability and fatigue indicates a role of the cerebellum in the perception of fatigue, which might come at the expense of motor control.SIGNIFICANCE STATEMENT Fatigue is one of the most common and debilitating symptoms in neurologic, neuropsychiatric, and chronic illnesses. Despite its epidemiological importance, there is a limited understanding of the neurophysiological mechanisms underlying fatigue. In a series of experiments, we demonstrate that decreased cerebellar excitability relates to lesser physical fatigue perception and worse motor control. These results showcase the role of the cerebellum in fatigue regulation and suggest that fatigue- and performance-related processes might compete for cerebellar resources.

Diagnostic Uncertainties in Tremor

The approach and diagnosis of patients with tremor may be challenging for clinicians. According to the most recent consensus statement by the Task Force on Tremor of the International Parkinson Movement Disorder Society, the differentiation between action (i.e., kinetic, postural, intention), resting, and other task- and position-specific tremors is crucial to this goal. In addition, patients with tremor must be carefully examined for other relevant features, including the topography of the tremor, since it can involve different body areas and possibly associate with neurological signs of uncertain significance. Following the characterization of major clinical features, it may be useful to define, whenever possible, a particular tremor syndrome and to narrow down the spectrum of possible etiologies. First, it is important to distinguish between physiological and pathological tremor, and, in the latter case, to differentiate between the underlying pathological conditions. A correct approach to tremor is particularly relevant for appropriate referral, counseling, prognosis definition, and therapeutic management of patients. The purpose of this review is to outline the possible diagnostic uncertainties that may be encountered in clinical practice in the approach to patients with tremor. In addition to an emphasis on a clinical approach, this review discusses the important ancillary role of neurophysiology and innovative technologies, neuroimaging, and genetics in the diagnostic process.

Suppression of Axial Tremor by Deep Brain Stimulation in Patients with Essential Tremor: Effects on Gait and Balance Measures

Background:

Deep brain stimulation (DBS) of the ventralis intermedius (VIM) nucleus of the thalamus has been successful in mitigating upper limb tremor, but the effect on gait and balance performance is unclear. Here, we aim to examine the effectiveness of VIM DBS on stride length variability, sway path length, and task-relevant tremor of various body segments in essential tremor (ET).

Methods:

Seventeen ET individuals treated with DBS (ET DBS) and 17 age-and sex-matched healthy controls (HC) performed a postural balance and overground walking task. In separate and consecutive visits, ET DBS performed gait and balance tasks with DBS ON or OFF. The main outcome measures were sway path length, stride length variability, and tremor quantified from upper limb, lower limb, upper and lower trunk (axial) during the gait and balance tasks.

Results:

With DBS OFF, ET DBS exhibited significantly greater stride length variability, sway path length, and tremor during gait and balance task relative to HC. Relative to DBS OFF, DBS ON reduced stride length variability and sway path length in ET DBS. The DBS-induced reduction in stride length variability was associated with the reduction in both upper trunk tremor and upper limb tremor. The DBS-induced reduction in sway path length was associated with the reduction in upper trunk tremor.

Discussion:

The findings of this study revealed that VIM DBS was effective in improving gait and balance in ET DBS and that improvements in gait and postural balance were associated with a reduction of axial tremor during the tasks.

Highlights:

Connecting tremors - a circuits perspective

PURPOSE OF REVIEW

Tremor is one of the most prevalent movement disorders in clinical practice. Here, we review new insights in the pathophysiology of tremor. We focus on the three most common tremor disorders: essential tremor (ET), dystonic tremor syndrome (DTS), and Parkinson's disease (PD) tremor.

RECENT FINDINGS

Converging evidence suggests that ET, DTS, and PD tremor are all associated with (partly) overlapping cerebral networks involving the basal ganglia and cerebello-thalamo-cortical circuit. Recent studies have assessed the role of these networks in tremor by measuring tremor-related activity and connectivity with electrophysiology and neuroimaging, and by perturbing network components using invasive and noninvasive brain stimulation. The cerebellum plays a more dominant and causal role in action tremors than in rest tremor, as exemplified by recent findings in ET, DTS, and re-emergent tremor in PD. Furthermore, the role of the cerebellum in DTS is related to clinical differences between patients, for example, whether or not the tremor occurs in a dystonic limb, and whether the tremor is jerky or sinusoidal.

SUMMARY

Insight into the pathophysiological mechanisms of tremor may provide a more direct window into mechanism-based treatment options than either the etiology or the clinical phenotype of a tremor syndrome.

Assessing Additional Characteristics of Muscle Function With Digital Handgrip Dynamometry and Accelerometry: Framework for a Novel Handgrip Strength Protocol

Maximal handgrip strength (HGS) is a convenient and reliable, but incomplete, assessment of muscle function. Although low HGS is a powerful predictor of poor health, several limitations to maximal HGS exist. The predictive value of HGS is restricted because low HGS is associated with a wide range of unspecified health conditions, and other characteristics of muscle function aside from strength capacity are not evaluated. Current HGS protocol guidelines emphasize the ascertainment of maximal force, which is only a single muscle function characteristic. Muscle function is intrinsically multivariable, and assessing other attributes in addition to strength capacity will improve screenings for age-related disabilities and diseases. Digital handgrip dynamometers and accelerometers provide unique opportunities to examine several aspects of muscle function beyond strength capacity, while also maintaining procedural ease. Specifically, digital handgrip dynamometry and accelerometry can assess the rate of force development, submaximal force steadiness, fatigability, and task-specific tremoring. Moreover, HGS protocols can be easily refined to include an examination of strength asymmetry and bilateral strength. Therefore, evaluating muscle function with new HGS technologies and protocols may provide a more comprehensive assessment of muscle function beyond maximal strength, without sacrificing feasibility. This Special Article introduces a novel framework for assessing multiple attributes of muscle function with digital handgrip dynamometry, accelerometry, and refinements to current HGS protocols. Such framework may aid in the discovery of measures that better predict and explain age-related disability, biological aging, and the effects of comorbid diseases that are amenable to interventions. These additional HGS measures may also contribute to our understanding of concepts such as resilience. Using sophisticated HGS technologies that are currently available and modernizing protocols for developing a new muscle function assessment may help transform clinical practice by enhancing screenings that will better identify the onset and progression of the disabling process.

Older adults use a motor plan that is detrimental to endpoint control

Here, we aimed to understand if older adults (OA) use a unique motor plan that is detrimental to endpoint control. We performed two experiments that used ankle ballistic contractions that reversed at the target. In Experiment 1, eight young adults (YA; 27.1 ± 4.2) and eight OA (73.3 ± 4.5) aimed to perform an ankle dorsiflexion-plantarflexion movement that reversed at 9° in 180 ms (target). We found that the coordination pattern (motor plan) differed for the two groups. OA used significantly greater soleus (SOL) activity to reverse the ankle movement than YA and exhibited greater tibialis anterior (TA) muscle activity variability (p < 0.05). OA exhibited worse endpoint control than YA, which associated with the exacerbated TA variability (R² > 0.2; p < 0.01). Experiment 2 aimed to confirm that the OA motor plan was detrimental to endpoint control. Fifteen YA (20.5 ± 1.4) performed an ankle dorsiflexion-plantarflexion contraction that reversed at 30% MVC in 160 ms by using either a pattern that mimicked OA (High SOL) or YA (Low SOL). With the High SOL coordination pattern, YA exhibited impaired endpoint control and greater TA activation variability. These findings provide strong evidence that OA select a unique motor plan that is detrimental to endpoint control.

Decomposition of Reaching Movements Enables Detection and Measurement of Ataxia

Technologies that enable frequent, objective, and precise measurement of ataxia severity would benefit clinical trials by lowering participation barriers and improving the ability to measure disease state and change. We hypothesized that analyzing characteristics of sub-second movement profiles obtained during a reaching task would be useful for objectively quantifying motor characteristics of ataxia. Participants with ataxia (N=88), participants with parkinsonism (N=44), and healthy controls (N=34) performed a computer tablet version of the finger-to-nose test while wearing inertial sensors on their wrists. Data features designed to capture signs of ataxia were extracted from participants' decomposed wrist velocity time-series. A machine learning regression model was trained to estimate overall ataxia severity, as measured by the Brief Ataxia Rating Scale (BARS). Classification models were trained to distinguish between ataxia participants and controls and between ataxia and parkinsonism phenotypes. Movement decomposition revealed expected and novel characteristics of the ataxia phenotype. The distance, speed, duration, morphology, and temporal relationships of decomposed movements exhibited strong relationships with disease severity. The regression model estimated BARS with a root mean square error of 3.6 points, r² = 0.69, and moderate-to-excellent reliability. Classification models distinguished between ataxia participants and controls and ataxia and parkinsonism phenotypes with areas under the receiver-operating curve of 0.96 and 0.89, respectively. Movement decomposition captures core features of ataxia and may be useful for objective, precise, and frequent assessment of ataxia in home and clinic environments.

Quantifying Tremor in Essential Tremor Using Inertial Sensors-Validation of an Algorithm

Background Assessment of essential tremor is often done by a trained clinician who observes the limbs during different postures and actions and subsequently rates the tremor. While this method has been shown to be reliable, the inter- and intra-rater reliability and need for training can make the use of this method for symptom progression difficult. Many limitations of clinical rating scales can potentially be overcome by using inertial sensors, but to date many algorithms designed to quantify tremor have key limitations. Methods We propose a novel algorithm to characterize tremor using inertial sensors. It uses a two-stage approach that 1) estimates the tremor frequency of a subject and only quantifies tremor near that range; 2) estimates the tremor amplitude as the portion of signal power above baseline activity during recording, allowing tremor estimation even in the presence of other activity; and 3) estimates tremor amplitude in physical units of translation (cm) and rotation (°), consistent with current tremor rating scales. We validated the algorithm technically using a robotic arm and clinically by comparing algorithm output with data reported by a trained clinician administering a tremor rating scale to a cohort of essential tremor patients. Results Technical validation demonstrated rotational amplitude accuracy better than ±0.2 degrees and position amplitude accuracy better than ±0.1 cm. Clinical validation revealed that both rotation and position components were significantly correlated with tremor rating scale scores. Conclusion We demonstrate that our algorithm can quantify tremor accurately even in the presence of other activities, perhaps providing a step forward for at-home monitoring.

Dysmetria and Errors in Predictions: The Role of Internal Forward Model

The terminology of cerebellar dysmetria embraces a ubiquitous symptom in motor deficits, oculomotor symptoms, and cognitive/emotional symptoms occurring in cerebellar ataxias. Patients with episodic ataxia exhibit recurrent episodes of ataxia, including motor dysmetria. Despite the consensus that cerebellar dysmetria is a cardinal symptom, there is still no agreement on its pathophysiological mechanisms to date since its first clinical description by Babinski. We argue that impairment in the predictive computation for voluntary movements explains a range of characteristics accompanied by dysmetria. Within this framework, the cerebellum acquires and maintains an internal forward model, which predicts current and future states of the body by integrating an estimate of the previous state and a given efference copy of motor commands. Two of our recent studies experimentally support the internal-forward-model hypothesis of the cerebellar circuitry. First, the cerebellar outputs (firing rates of dentate nucleus cells) contain predictive information for the future cerebellar inputs (firing rates of mossy fibers). Second, a component of movement kinematics is predictive for target motions in control subjects. In cerebellar patients, the predictive component lags behind a target motion and is compensated with a feedback component. Furthermore, a clinical analysis has examined kinematic and electromyography (EMG) features using a task of elbow flexion goal-directed movements, which mimics the finger-to-nose test. Consistent with the hypothesis of the internal forward model, the predictive activations in the triceps muscles are impaired, and the impaired predictive activations result in hypermetria (overshoot). Dysmetria stems from deficits in the predictive computation of the internal forward model in the cerebellum. Errors in this fundamental mechanism result in undershoot (hypometria) and overshoot during voluntary motor actions. The predictive computation of the forward model affords error-based motor learning, coordination of multiple degrees of freedom, and adequate timing of muscle activities. Both the timing and synergy theory fit with the internal forward model, microzones being the elemental computational unit, and the anatomical organization of converging inputs to the Purkinje neurons providing them the unique property of a perceptron in the brain. We propose that motor dysmetria observed in attacks of ataxia occurs as a result of impaired predictive computation of the internal forward model in the cerebellum.