Eye movement disorders in inborn errors of metabolism: A quantitative analysis of 37 patients.

Inborn errors of metabolism are genetic disorders that need to be recognized as early as possible because treatment may be available. In late-onset forms, core symptoms are movement disorders, psychiatric symptoms, and cognitive impairment. Eye movement disorders are considered to be frequent too, although specific knowledge is lacking. We describe and analyze eye movements in patients with an inborn error of metabolism, and see whether they can serve as an additional clue in the diagnosis of particularly late-onset inborn errors of metabolism. Demographics, disease characteristics, and treatment data were collected. All patients underwent a standardized videotaped neurological examination and a video-oculography. Videos are included. We included 37 patients with 15 different inborn errors of metabolism, including 18 patients with a late-onset form. With the exception of vertical supranuclear gaze palsy in Niemann-Pick type C and external ophthalmolplegia in Kearns-Sayre syndrome, no relation was found between the type of eye movement disorder and the underlying metabolic disorder. Movement disorders were present in 29 patients (78%), psychiatric symptoms in 14 (38%), and cognitive deficits in 26 patients (70%). In 87% of the patients with late-onset disease, eye movement disorders were combined with one or more of these core symptoms. To conclude, eye movement disorders are present in different types of inborn errors of metabolism, but are often not specific to the underlying disorder. However, the combination of eye movement disorders with movement disorders, psychiatric symptoms, or cognitive deficits can serve as a diagnostic clue for an underlying late-onset inborn error of metabolism.

The development of consistency and flexibility in manual pointing during middle childhood.

Goal-directed actions become truly functional and skilled when they are consistent yet flexible. In manual pointing, end-effector consistency is characterized by the end position of the index fingertip, whereas flexibility in movement execution is captured by the use of abundant arm-joint configurations not affecting the index finger end position. Because adults have been shown to exploit their system's flexibility in challenging conditions, we wondered whether during middle childhood children are already able to exploit motor flexibility when demanded by the situation. We had children aged 5-10 years and adults perform pointing movements in a nonchallenging and challenging condition. Results showed that end-effector errors and flexibility in movement execution decreased with age. Importantly, only the 9-10-year-olds and adults showed increased flexibility in the challenging condition. Thus, while consistency increases and flexibility decreases during mid-childhood development, from the age of nine children appear able to employ more flexibility with increasing task demands.

Next move in movement disorders (NEMO): developing a computer-aided classification tool for hyperkinetic movement disorders.

INTRODUCTION: Our aim is to develop a novel approach to hyperkinetic movement disorder classification, that combines clinical information, electromyography, accelerometry and video in a computer-aided classification tool. We see this as the next step towards rapid and accurate phenotype classification, the cornerstone of both the diagnostic and treatment process. METHODS AND ANALYSIS: The Next Move in Movement Disorders (NEMO) study is a cross-sectional study at Expertise Centre Movement Disorders Groningen, University Medical Centre Groningen. It comprises patients with single and mixed phenotype movement disorders. Single phenotype groups will first include dystonia, myoclonus and tremor, and then chorea, tics, ataxia and spasticity. Mixed phenotypes are myoclonus-dystonia, dystonic tremor, myoclonus ataxia and jerky/tremulous functional movement disorders. Groups will contain 20 patients, or 40 healthy participants. The gold standard for inclusion consists of interobserver agreement on the phenotype among three independent clinical experts. Electromyography, accelerometry and three-dimensional video data will be recorded during performance of a set of movement tasks, chosen by a team of specialists to elicit movement disorders. These data will serve as input for the machine learning algorithm. Labels for supervised learning are provided by the expert-based classification, allowing the algorithm to learn to predict what the output label should be when given new input data. Methods using manually engineered features based on existing clinical knowledge will be used, as well as deep learning methods which can detect relevant and possibly new features. Finally, we will employ visual analytics to visualise how the classification algorithm arrives at its decision. ETHICS AND DISSEMINATION: Ethical approval has been obtained from the relevant local ethics committee. The NEMO study is designed to pioneer the application of machine learning of movement disorders. We expect to publish articles in multiple related fields of research and patients will be informed of important results via patient associations and press releases.

Task constraints act at the level of synergies and at the level of end-effector kinematics in manual reaching and manual lateral interception.

To coordinate the redundant degrees of freedom (DOF) in the action system, synergies are often proposed. Synergies organize DOF in temporary task-specific units emerging from interactions among task, organism, and environmental constraints. We examined whether task constraints affect synergies, end-effector kinematics, or both. To this end, we compared synergies and end-effector kinematics when participants (N = 15) performed discrete movements of identical amplitude in manual reaching (stationary targets) and manual lateral interception (moving targets, with different angles of approach). We found that time-velocity profiles were roughly symmetric in reaching, whereas they had a longer decelerative tail and showed an angle-of-approach effect in interception. Uncontrolled manifold analyses showed that in all conditions joint angle variability was primarily covariation, indicating a synergistic organization. The analysis on the clusters of joint angle configurations demonstrated differences between reaching and interception synergies, whereas more similar synergies were used within interception conditions. This implies that some task constraints operate at the level of synergies while other task constraints only affect end-effector kinematics. The results support a 2-step process in the organization of DOF, consisting of synergy formation and further constraining of synergies to produce the actual movement, as proposed by Kay (1988). (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Comparing Different Methods to Create a Linear Model for Uncontrolled Manifold Analysis.

An essential step in uncontrolled manifold analysis is creating a linear model that relates changes in elemental variables to changes in performance variables. Such linear models are usually created by means of an analytical method. However, a multiple regression analysis is also suggested. Whereas the analytical method includes only averages of joint angles, the regression method uses the distribution of all joint angles. We examined whether the latter model is more suitable to describe manual reaching movements. The relation between estimated and measured fingertip-position deviations from the mean of individual trials, the relation between fingertip variability and nongoal-equivalent variability, goal-equivalent variability, and nongoal-equivalent variability indicated that the linear model created with the regression method gives a more accurate description of the reaching data. Therefore, we suggest the usage of the regression method to create the linear model for uncontrolled manifold analysis in tasks that require the approximation of the linear model.

Does practicing a wide range of joint angle configurations lead to higher flexibility in a manual obstacle-avoidance target-pointing task?

Flexibility in motor actions can be defined as variability in the use of degrees of freedom (e.g., joint angles in the arm) over repetitions while keeping performance (e.g., fingertip position) stabilized. We examined whether flexibility can be increased through enlarging the joint angle range during practice in a manual obstacle-avoidance target-pointing task. To establish differences in flexibility we partitioned the variability in joint angles over repetitions in variability within (GEV) and variability outside the solution space (NGEV). More GEV than NGEV reflects flexibility; when the ratio of the GEV and NGEV is higher, flexibility is higher. The pretest and posttest consisted of 30 repetitions of manual pointing to a target while moving over a 10 cm high obstacle. To enlarge the joint angle range during practice participants performed 600 target-pointing movements while moving over obstacles of different heights (5-9 cm, 11-15 cm). The results indicated that practicing movements over obstacles of different heights led participants to use enlarged range of joint angles compared to the range of joint angles used in movements over the 10 cm obstacle in the pretest. However, for each individual obstacle neither joint angle variance nor flexibility were higher during practice. We also did not find more flexibility after practice. In the posttest, joint angle variance was in fact smaller than before practice, primarily in GEV. The potential influences of learning effects and the task used that could underlie the results obtained are discussed. We conclude that with this specific type of practice in this specific task, enlarging the range of joint angles does not lead to more flexibility.