Additive Effects of Prior Knowledge and Predictive Visual Information in Improving Continuous Tracking Performance

Abstract

Visual information and prior knowledge represent two different sources of predictability for tasks which each have been reported to have a beneficial effect on dual-task performance. What if the two were combined? Adding multiple sources of predictability might, on the one hand, lead to additive, beneficial effects on dual-tasking. On the other hand, it is conceivable that multiple sources of predictability do not increase dual-task performance further, as they complicate performance due to having to process information from multiple sources. In this study, we combined two sources of predictability, predictive visual information and prior knowledge (implicit learning and explicit learning) in a dual-task setup. 22 participants performed a continuous tracking task together with an auditory reaction time task over three days. The middle segment of the tracking task was repeating to promote motor learning, but only half of the participants was informed about this. After the practice blocks (day 3), we provided participants with predictive visual information about the tracking path to test whether visual information would add to beneficial effects of prior knowledge (additive effects of predictability). Results show that both predictive visual information and prior knowledge improved dual-task performance, presented simultaneously or in absence of each other. These results show that processing of information relevant for enhancement of task performance is unhindered by dual-task demands.

Individual differences fill the uncharted intersections between cognitive structure, flexibility, and plasticity in multitasking.

“…Beyond, we also find evidence for individual differences in flexibility affecting cognitive structure. For instance, some types of dual tasks allow task integration which eventually helps to reduce or even circumvent structural limitations (e.g., Broeker et al, 2020; de Oliveira et al, 2017). Participants who practiced a tracking task and an auditory response task, reduced costs in both tasks once the auditory task was tempo-spatially coupled to the tracking task (Broeker et al, 2021): Whenever the sounds of the auditory task did not occur in random intervals along the tracking path, but shortly before tracking turns, all participants improved tracking accuracy and RTs.…”

TRACK—a new algorithm and open-source tool for the analysis of pursuit-tracking sensorimotor integration processes

“…The pursuit-tracking paradigm offers a continuous and complex experimental setting used to examine sensorimotor integration processes in more ecologically valid settings (Broeker, Ewolds, et al, 2020a;Broeker, Haeger, et al, 2020b;Hill, 2009Hill, , 2014Hill & Raab, 2005;Parker et al, 2020;Pew, 1974;Sekiya, 2006;Wulf & Schmidt, 1997). In a typical pursuit-tracking task, participants watch a target moving along an (invisible) trajectory.…”

“…In particular, the choice of a useful metric to access continuous behavioral adjustments crucially depends on the device operated by the participants. Pursuit-tracking tasks are often executed using a joystick (Broeker et al, 2021;Broeker, Ewolds, et al, 2020a;Broeker, Haeger, et al, 2020b;Ewolds et al, 2017Ewolds et al, , 2021Hill, 2014;Künzell et al, 2016). Importantly, in such studies, participants can usually only control the vertical movement of the cursor.…”

“…Importantly, in such studies, participants can usually only control the vertical movement of the cursor. Often, the horizontal motion is fixed to the target (i.e., x-axis speed of target and cursor are aligned) to prevent participants from cutting trials short by moving the cursor straight to the aimed edge of the screen (Broeker, Ewolds, et al, 2020a;Broeker, Haeger, et al, 2020b). In contrast, in studies using other devices, such as a computer mouse, participants can often control the horizontal as well as vertical movement of the cursor (Hill, 2014;Raab et al, 2013;Zhu et al, 2014).…”

“…Consequently, neurophysiological insights into continuous tracking performance are subject to ambiguity. While in some studies this way of analyzing the tracking data is sufficient to detect global differences in performance, such as the enhanced tracking performance during the repeated trajectory part that is induced by implicit learning (Ewolds et al, 2021;Künzell et al, 2016;Wulf & Schmidt, 1997) or related to higher predictability of the target trajectory (Broeker et al, 2021), the increase in the tracking error with time spent on task (Zhu et al, 2014) or the increased tracking performance if there is prior knowledge about the repeated trajectory (Broeker, Ewolds, et al, 2020a). In sum, the RMSE does not fully exhaust the potential and complexity of the data.…”