Center for Language Evolution, PPLS, University of Edinburgh, Dugald Stewart Building, Edinburgh, EH8 9AD, United Kingdom.
Laboratoire de Linguistique Formelle, Université Paris Diderot, Sorbonne Paris Cité, CNRS, Paris, France.
Behav Res Methods. 2019 Jun;51(3):1085-1101. doi: 10.3758/s13428-018-01194-x.
Mouse tracking promises to be an efficient method to investigate the dynamics of cognitive processes: It is easier to deploy than eyetracking, yet in principle it is much more fine-grained than looking at response times. We investigated these claimed benefits directly, asking how the features of decision processes-notably, decision changes-might be captured in mouse movements. We ran two experiments, one in which we explicitly manipulated whether our stimuli triggered a flip in decision, and one in which we replicated more ecological, classical mouse-tracking results on linguistic negation (Dale & Duran, Cognitive Science, 35, 983-996, 2011). We concluded, first, that spatial information (mouse path) is more important than temporal information (speed and acceleration) for detecting decision changes, and we offer a comparison of the sensitivities of various typical measures used in analyses of mouse tracking (area under the trajectory curve, direction flips, etc.). We do so using an "optimal" analysis of our data (a linear discriminant analysis explicitly trained to classify trajectories) and see what type of data (position, speed, or acceleration) it capitalizes on. We also quantify how its results compare with those based on more standard measures.
它比眼动追踪更容易部署，但原则上它比观察反应时间要精细得多。我们直接研究了这些声称的好处，探讨了决策过程的特征——尤其是决策变化——如何在鼠标移动中得到体现。我们进行了两项实验，一项实验中我们明确地操纵了我们的刺激是否会引发决策的转变，另一项实验中我们复制了更多关于语言否定的生态、经典鼠标追踪结果（Dale & Duran，《认知科学》，35，983-996，2011）。我们的结论是，首先，对于检测决策变化，空间信息（鼠标轨迹）比时间信息（速度和加速度）更重要，我们还比较了各种典型的鼠标追踪分析中使用的测量方法的灵敏度（轨迹曲线下的面积、方向翻转等）。我们使用数据的“最优”分析（一种明确训练来分类轨迹的线性判别分析）来实现这一点，并了解它利用了哪种类型的数据（位置、速度或加速度）。我们还量化了它的结果与基于更标准测量方法的结果相比如何。
