ReActLab: A Custom Framework for Sensorimotor Experiments “in-the-wild”

Abstract

Over the last few years online platforms for running psychology experiments beyond simple questionnaires and surveys have become increasingly popular. This trend has especially increased after many laboratory facilities had to temporarily avoid in-person data collection following COVID-19-related lockdown regulations. Yet, while offering a valid alternative to in-person experiments in many cases, platforms for online experiments are still not a viable solution for a large part of human-based behavioral research. Two situations in particular pose challenges: First, when the research question requires design features or participant interaction which exceed the customization capability provided by the online platform; and second, when variation among hardware characteristics between participants results in an inadmissible confounding factor. To mitigate the effects of these limitations, we developed ReActLab (Remote Action Laboratory), a framework for programming remote, browser-based experiments using freely available and open-source JavaScript libraries. Since the experiment is run entirely within the browser, our framework allows for portability to any operating system and many devices. In our case, we tested our approach by running experiments using only a specific model of Android tablet. Using ReActLab with this standardized hardware allowed us to optimize our experimental design for our research questions, as well as collect data outside of laboratory facilities without introducing setup variation among participants. In this paper, we describe our framework and show examples of two different experiments carried out with it: one consisting of a visuomotor adaptation task, the other of a visual localization task. Through comparison with results obtained from similar tasks in in-person laboratory settings, we discuss the advantages and limitations for developing browser-based experiments using our framework.

Predictors of sensorimotor adaption: insights from over 100,000 reaches

“…Our data-driven web-based approach offers a powerful method to study sensorimotor learning outside the traditional laboratory (also see: (83,(88)(89)(90)(91)(92)(93)(94)(95)(96)(97)(98)(99)). First, we have shown that these data are reliable and valid, reproducing classic findings in the literature.…”

Age-related changes in motor planning for prior intentions: a mouse tracking reach-to-click task

“…While few studies used computer mouse tracking to study movement planning, it has been used in a wide range of domains in the psychological and behavioral sciences ( Freeman, 2018 ; Schoemann et al, 2021 ). More recently, the computer mouse has been used as a valid tool to study motor adaptation and sensorimotor learning ( Lee et al, 2016 ; Avraham et al, 2021 ; Listman et al, 2021 ; Tsay et al, 2021 , 2023 ; Balestrucci et al, 2022 ; Donovan et al, 2022 ; Weightman et al, 2022 ) across a wide age range from 18 to 70 ( Tsay et al, 2023 ). It has been found such data collected through computer mouse are reliable, valid, and able to reproduce classic findings as in the literature examined 3D real-world hand movements, even among children between 9 and 16 ( Malone et al, 2023 ), older people with and without Parkinson’s disease ( Tsay et al, 2022 ) and individuals with impaired visual function ( Tsay et al, 2023 ).…”