Personalized Speed of Processing Training Online (pSOPT Online): A General Cloud-based Framework for Personalized Speed of Processing Training Tasks

Abstract

Speed of processing training (SOPT) is a well-known nonverbal, computerized program that involves the repeated practice of tasks with increased difficulty that aim to improve speed and attention. While learning in SOPT targets neural circuits that underpin multiple cognitive domains, the effects on cognitive function are relatively selective and transitory. To enhance the benefits of SOPT, recent cognitive intervention approaches emphasize the importance of personalization to address individual heterogeneity in response to cognitive challenges.In this paper, we present personalized SOPT (pSOPT) Online, a novel cloud-based framework to integrate SOPT tasks with advanced personalization engines that tune the task complexity to the trainee’s real-time adaptation capacity. pSOPT Online defines different building blocks for the creation of cloud-based SOPT tasks, personalization engines, physiological measurement devices, and a RESTful web API that defines the interaction between the different components. We then present four SOPT tasks and one personalization engine developed using the framework. Finally, we present initial results from a small-scale beta test that will guide subsequent framework refinement before large-scale randomized testing.