There has been much debate concerning whether startling sensory stimuli can activate a fast‐neural pathway for movement triggering (StartReact) which is different from that of voluntary movements. Activity in sternocleidomastoid (SCM) electromyogram is suggested to indicate activation of this pathway. We evaluated whether SCM activity can accurately identify trials which may differ in their neurophysiological triggering and assessed the use of cumulative distribution functions (CDFs) of reaction time (RT) data to identify trials with the shortest RTs for analysis. Using recent data sets from the StartReact literature, we examined the relationship between RT and SCM activity. We categorised data into short/longer RT bins using CDFs and used linear mixed‐effects models to compare potential conclusions that can be drawn when categorising data on the basis of RT versus on the basis of SCM activity. The capacity of SCM to predict RT is task‐specific, making it an unreliable indicator of distinct neurophysiological mechanisms. Classification of trials using CDFs is capable of capturing potential task‐ or muscle‐related differences in triggering whilst avoiding the pitfalls of the traditional SCM activity‐based classification method. We conclude that SCM activity is not always evident on trials that show the early triggering of movements seen in the StartReact phenomenon. We further propose that a more comprehensive analysis of data may be achieved through the inclusion of CDF analyses. These findings have implications for future research investigating movement triggering as well as for potential therapeutic applications of StartReact.

中文翻译：

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累积分布函数：一种替代方法，用于检查StartReact效果中准备好的运动动作的触发

关于令人震惊的感觉刺激是否可以激活运动触发的快速神经通路（StartReact），与自愿运动不同，存在很多争论。建议在胸锁乳突肌（SCM）肌电图中进行活动以指示该途径的激活。我们评估了SCM活动是否可以准确识别出可能在其神经生理触发方面不同的试验，并评估了反应时间（RT）数据的累积分布函数（CDF）的使用，以鉴定分析时间最短的RTs。使用来自StartReact文献的最新数据集，我们检查了RT和SCM活动之间的关系。我们使用CDF将数据分为短/长RT仓，并使用线性混合效应模型来比较根据RT与SCM活动对数据进行分类时可以得出的潜在结论。SCM预测RT的能力是特定于任务的，使其成为不同神经生理机制的不可靠指标。使用CDF进行的试验分类能够捕获潜在的任务或与肌肉相关的触发差异，同时避免了传统的基于SCM活动的分类方法的陷阱。我们得出结论，在表明StartReact现象中出现的动作的早期触发的试验中，SCM活动并不总是很明显。我们进一步建议，可以通过包含CDF分析来实现对数据的更全面分析。