Abstract：
Web-based experiments are gaining momentum in motor learning research because of the desire to increase statistical power, decrease overhead for human participant experiments, and utilize a more demographically inclusive sample population. However, there is a vital need to understand the general feasibility and considerations necessary to shift tightly controlled human participant experiments to an online setting. We developed and deployed an online experimental platform modeled after established in-laboratory visuomotor rotation experiments to serve as a case study examining remotely collected data quality for an 80-min experiment. Current online motor learning experiments have thus far not exceeded 60 min, and current online crowdsourced studies have a median duration of approximately 10 min. Thus, the impact of a longer-duration, web-based experiment is unknown. We used our online platform to evaluate perturbation-driven motor adaptation behavior under three rotation sizes (±10°, ±35°, and ±65°) and two sensory uncertainty conditions. We hypothesized that our results would follow predictions by the relevance estimation hypothesis. Remote execution allowed us to double (n = 49) the typical participant population size from similar studies. Subsequently, we performed an in-depth examination of data quality by analyzing single-trial data quality, participant variability, and potential temporal effects across trials. Results replicated in-laboratory findings and provided insight on the effect of induced sensory uncertainty on the relevance estimation hypothesis. Our experiment also highlighted several specific challenges associated with online data collection including potentially smaller effect sizes, higher data variability, and lower recommended experiment duration thresholds. Overall, online paradigms present both opportunities and challenges for future motor learning research.
摘要：
基于网络的实验在运动学习研究中获得了势头，因为人们渴望增加统计能力，减少人类参与者实验的开销，并利用更具人口统计学包容性的样本人群。然而,有一个至关重要的需要了解的一般可行性和必要的考虑因素，转移严格控制人类参与者的实验到一个在线设置。我们开发并部署了一个在线实验平台，该平台是在建立了实验室视觉运动旋转实验后建模的，以作为一个案例研究，检查80分钟实验的远程收集数据质量。目前的在线运动学习实验到目前为止还没有超过60分钟，目前的在线众包研究的中位持续时间约为10分钟。因此，持续时间较长的影响，基于网络的实验是未知的。我们使用我们的在线平台来评估三种旋转大小（±10°，±35°,和±65°)和两个感官不确定度条件。我们假设我们的结果将遵循相关性估计假设的预测。远程执行使我们能够将类似研究的典型参与者人数增加一倍（n=49）。随后，我们通过分析单试验数据质量对数据质量进行了深入的检查，参与者变异性，以及整个试验的潜在时间效应。结果复制了实验室的发现，并提供了有关诱导的感觉不确定性对相关性估计假设的影响的见解。我们的实验还强调了与在线数据收集相关的几个具体挑战，包括可能较小的效应大小。更高的数据可变性，和较低的推荐实验持续时间阈值。总的来说,在线范式为未来的运动学习研究提供了机遇和挑战。
