Highlights Feature Binding/integration in the motor domain in Tourette Syndrome (TS) is examined. Motor binding processes and interleaved action are intact in TS. Binding processes are differentially modulated in the motor domain and sensori-motor processes.
Premonitory urges preceding tics are a cardinal feature of Gilles de la Tourette syndrome (GTS), a developmental disorder usually starting during middle childhood. However, the temporal relation between urges and tics has only been investigated in adults. In 25 children and adolescents with GTS (8–18 years), we assess urge-tic associations, including inter-individual differences, correlation to clinical measures, and in comparison to a previously reported sample of adult GTS patients. Group-level analyses confirmed positive associations between urges and tics. However, at the individual level, less than half of participants showed positive associations, a similar proportion did not, and in two participants, the association was reversed. Tic expression and subjective urge levels correlated with corresponding clinical scores and participants with more severe tics during the urge monitor exhibited stronger urge-tic associations. Associations between reported urge levels and instantaneous tic intensity tended to be less pronounced in children and adolescents than in adult GTS patients. The observed heterogeneity of urge-tic associations cast doubt on the notion that tics are directly caused by urges. More severe tics may facilitate anticipation of tics and thereby lead to more pronounced urge-tic associations, consistent with a hypothesis of urges as a byproduct of tics.
Tics in Tourette syndrome are often difficult to discern from single spontaneous movements or vocalizations in healthy people. In the present study, videos of patients with Tourette syndrome and healthy controls were taken and independently scored according to the Modified Rush Videotape Rating Scale. We included n = 101 patients with Tourette syndrome (71 males, 30 females, mean age 17.36 years ± 10.46 standard deviation) and n = 109 healthy controls (57 males, 52 females, mean age 17.62 years ± 8.78 standard deviation) in a machine learning-based analysis. The results showed that the severity of motor tics, but not vocal phenomena, is the best predictor to separate and classify patients with Tourette syndrome and healthy controls. This finding questions the validity of current diagnostic criteria for Tourette syndrome requiring the presence of both motor and vocal tics. In addition, the negligible importance of vocalizations has implications for medical practice, because current recommendations for Tourette syndrome probably also apply to the large group with chronic motor tic disorders.
It is a common phenomenon that somatosensory sensations can trigger actions to alleviate experienced tension. Such “urges” are particularly relevant in patients with Gilles de la Tourette (GTS) syndrome since they often precede tics, the cardinal feature of this common neurodevelopmental disorder. Altered sensorimotor integration processes in GTS as well as evidence for increased binding of stimulus- and response-related features (“hyper-binding”) in the visual domain suggest enhanced perception–action binding also in the somatosensory modality. In the current study, the Theory of Event Coding (TEC) was used as an overarching cognitive framework to examine somatosensory-motor binding. For this purpose, a somatosensory-motor version of a task measuring stimulus–response binding (S-R task) was tested using electro-tactile stimuli. Contrary to the main hypothesis, there were no group differences in binding effects between GTS patients and healthy controls in the somatosensory-motor paradigm. Behavioral data did not indicate differences in binding between examined groups. These data can be interpreted such that a compensatory “downregulation” of increased somatosensory stimulus saliency, e.g., due to the occurrence of somatosensory urges and hypersensitivity to external stimuli, results in reduced binding with associated motor output, which brings binding to a “normal” level. Therefore, “hyper-binding” in GTS seems to be modality-specific.
Background Video‐based tic detection and scoring is useful to independently and objectively assess tic frequency and severity in patients with Tourette syndrome. In trained raters, interrater reliability is good. However, video ratings are time‐consuming and cumbersome, particularly in large‐scale studies. Therefore, we developed two machine learning (ML) algorithms for automatic tic detection. Objective The aim of this study was to evaluate the performances of state‐of‐the‐art ML approaches for automatic video‐based tic detection in patients with Tourette syndrome. Methods We used 64 videos of n = 35 patients with Tourette syndrome. The data of six subjects (15 videos with ratings) were used as a validation set for hyperparameter optimization. For the binary classification task to distinguish between tic and no‐tic segments, we established two different supervised learning approaches. First, we manually extracted features based on landmarks, which served as input for a Random Forest classifier (Random Forest). Second, a fully automated deep learning approach was used, where regions of interest in video snippets were input to a convolutional neural network (deep neural network). Results Tic detection F1 scores (and accuracy) were 82.0% (88.4%) in the Random Forest and 79.5% (88.5%) in the deep neural network approach. Conclusions ML algorithms for automatic tic detection based on video recordings are feasible and reliable and could thus become a valuable assessment tool, for example, for objective tic measurements in clinical trials. ML algorithms might also be useful for the differential diagnosis of tics. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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