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<p>While considered a motor control structure, the cerebellum contributes to non-motor functions, including impulsivity. However, whether it contributes to impulsivity in a domain-specific manner remains unknown. Studies on cerebellar ataxia (CA), a common model for cerebellar dysfunction, typically have small sample sizes, limiting robustness. In a multicenter cross-sectional study, we investigated the cerebellum’s role in various forms of impulsivity by comparing large cohorts of CA to age- and education-matched neurotypical healthy (NH) controls. Additionally, to examine the ability to identify individuals with CA using impulsivity features alone, we developed supervised machine learning (ML) models. In experiment 1 (CA = 140, NH = 136), impulsivity was assessed using the BIS-11 questionnaire. In experiment 2 (CA = 110, NH = 107), performance-based impulsivity was assessed using the MCQ-27, evaluating delay discounting in monetary decision-making. Two ML models—Logistic Regression and Random Forest—were utilized to classify disorder status (CA/NH). The CA group showed higher BIS-11 scores (<i>p</i> = 0.001), indicating higher impulsivity, driven by motor (<i>p</i> &lt; 0.001) and attention (<i>p</i> = 0.002) impulsivity. However, the CA group exhibited lower non-planning impulsivity (<i>p</i> = 0.014). In the MCQ-27, the CA group showed lower k-values (<i>p</i> &lt; 0.005), indicating reduced impulsivity in monetary decisions. Both ML models demonstrated strong classification performance (AUC ≥ 0.85) in independent datasets. This study highlights the cerebellum’s selective role in impulsivity. We found higher motor and attentional impulsivity in CA alongside lower non-planning and decision-making impulsivity. This suggests a unique impulsivity profile in CA that may indicate a compensatory mechanism for future events. ML models demonstrated high classification performance, suggesting impulsivity is a core non-motor feature of CA.</p>

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Impulsivity in cerebellar ataxia: an online, multidimensional assessment

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年9月13日

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  • Brooke Chasalow,
  • Yakov Flaumenhaft,
  • Yael De Picciotto,
  • Chi-Ying R. Lin,
  • Leila Montaser-Kouhsari,
  • William Saban

摘要

While considered a motor control structure, the cerebellum contributes to non-motor functions, including impulsivity. However, whether it contributes to impulsivity in a domain-specific manner remains unknown. Studies on cerebellar ataxia (CA), a common model for cerebellar dysfunction, typically have small sample sizes, limiting robustness. In a multicenter cross-sectional study, we investigated the cerebellum’s role in various forms of impulsivity by comparing large cohorts of CA to age- and education-matched neurotypical healthy (NH) controls. Additionally, to examine the ability to identify individuals with CA using impulsivity features alone, we developed supervised machine learning (ML) models. In experiment 1 (CA = 140, NH = 136), impulsivity was assessed using the BIS-11 questionnaire. In experiment 2 (CA = 110, NH = 107), performance-based impulsivity was assessed using the MCQ-27, evaluating delay discounting in monetary decision-making. Two ML models—Logistic Regression and Random Forest—were utilized to classify disorder status (CA/NH). The CA group showed higher BIS-11 scores (p = 0.001), indicating higher impulsivity, driven by motor (p < 0.001) and attention (p = 0.002) impulsivity. However, the CA group exhibited lower non-planning impulsivity (p = 0.014). In the MCQ-27, the CA group showed lower k-values (p < 0.005), indicating reduced impulsivity in monetary decisions. Both ML models demonstrated strong classification performance (AUC ≥ 0.85) in independent datasets. This study highlights the cerebellum’s selective role in impulsivity. We found higher motor and attentional impulsivity in CA alongside lower non-planning and decision-making impulsivity. This suggests a unique impulsivity profile in CA that may indicate a compensatory mechanism for future events. ML models demonstrated high classification performance, suggesting impulsivity is a core non-motor feature of CA.