Parkinsonism & related disorders · 2025
Eye blinking abnormalities in Tourette syndrome: Blink more or blink differently?
СтатьяНазвание и аннотация: Перевод в очереди
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Verrel Julius, Schappert Ronja, Brügge Nele, Rawish Tina, Bäumer Tobias, Hao Yifan, Stenger Roland, Beste Christian, Fudickar Sebastian, Roessner Veit, Münchau Alexander
Аннотация
INTRODUCTION: Blinking abnormalities are among the earliest and most common symptoms in Gilles de la Tourette syndrome (GTS) but have not been studied using precise quantitative methods. Here, we use automated video-based analyses to assess blinking abnormalities in GTS in terms of blink rates as well as alterations in spatiotemporal blink features.
METHODS: We analyzed 2.5-minute video recordings from age- and sex-matched adult GTS and healthy control (HC) samples (56 participants with 136 videos per group; 18-59 years). Eye aperture time series were used to detect blink events and extract blink features (amplitude, amplitude asymmetry, duration, inter-blink intervals). Individual blinks were categorized as "typical" or "atypical" relative to feature distributions from an independent HC sample.
RESULTS: Overall blink rates were twice as high in GTS compared to HC (34.1 vs. 17.3 blinks/minute). This difference was most pronounced for atypical blinks (10.8 vs. 1.9 atypical blinks/minute), even allowing high-accuracy classification of GTS vs. HC videos (83.1 %) using cross-validated logistic regression. Classification based on the rate of typical blinks, average blink features, or single feature deviation rates yielded considerably lower accuracies. On average, 58.7 % of atypical blinks of a given participant shared the same feature deviation, but the feature deviation patterns significantly varied between participants, as confirmed using permutation statistics.
CONCLUSION: Blinking abnormalities in GTS are best characterized by the frequency of atypical blinks, which appear to drive the overall increase in blink rate. Blinking abnormalities were consistent within but heterogeneous across individuals.
METHODS: We analyzed 2.5-minute video recordings from age- and sex-matched adult GTS and healthy control (HC) samples (56 participants with 136 videos per group; 18-59 years). Eye aperture time series were used to detect blink events and extract blink features (amplitude, amplitude asymmetry, duration, inter-blink intervals). Individual blinks were categorized as "typical" or "atypical" relative to feature distributions from an independent HC sample.
RESULTS: Overall blink rates were twice as high in GTS compared to HC (34.1 vs. 17.3 blinks/minute). This difference was most pronounced for atypical blinks (10.8 vs. 1.9 atypical blinks/minute), even allowing high-accuracy classification of GTS vs. HC videos (83.1 %) using cross-validated logistic regression. Classification based on the rate of typical blinks, average blink features, or single feature deviation rates yielded considerably lower accuracies. On average, 58.7 % of atypical blinks of a given participant shared the same feature deviation, but the feature deviation patterns significantly varied between participants, as confirmed using permutation statistics.
CONCLUSION: Blinking abnormalities in GTS are best characterized by the frequency of atypical blinks, which appear to drive the overall increase in blink rate. Blinking abnormalities were consistent within but heterogeneous across individuals.