Predictability improves dual-task performance: the effects of explicit and implicit learning

Predictability is increasingly recognized as an important principle in perception and motor learning. The pursuit of increased predictability seems to one of the main goals that the human system pursues. Therefore, providing predictability in one of the most challenging situations that humans face, namely multitasking, a promising line of research. In this thesis the impact of predictability was systematically investigated in five experiments. In the first four experiments predictability was achieved by implementing a repeating pattern in one task, or both tasks. Participants acquired knowledge of these patterns either explicitly or implicitly in several training sessions, under single-task or dual-task conditions. We tested whether this increased predictability helped dual-task performance after the training sessions. The results suggest that predictability is helpful for dual-task performance, although the benefits are confined to the predictable task itself. In a fifth experiment we focused on providing between task predictability, which led to a large performance improvement in both tasks, prompting the discussion about what constitutes a task, in the sense of when can two tasks be perceived as a single task comprising both, a theoretical problem we tried to tackle in one of the articles. Explanations for the findings, theoretical implications, methodological issues and suggestions for future research are given in the general discussio

Contributions of open-loop and closed-loop control in a continuous tracking task differ depending on attentional demands during practice

We provide tracking data of the analysed segments after filtering, cognitive performance data and indivdual force levels. To this end, the data set contains three zip-files of numbers of csv-files and an additional csv-file. In each csv-file, comma delimits information within the rows. Participant numbers range between 1 and 21 where the first 11 numbers always refer to the participants of the single-task training group and the final 10 numbers refer to the participants of the dual-task training group. The IndividualForceMaximum.csv includes separate rows of participant’s information about training group, individual force maximum, and the 10% value of the force maximum, which was important for adapting the required force to the individual applicable leg force. The CognitiveTaskData.zip contains four csv-files. Two files are for the TEST sessions, which include either the total number of responses or the number of correct responses per trial for each participant within a row. The other two files are for the TRAINING data (either total number of responses or number of correct responses) of the cognitive task for the participants of the dual-task training group. The file includes 15 trials of the first and the last five training days (i.e., days 1 to 5, and days 18 to 22). For each participant the training data is presented in a row. The tracking data is split with respect to the training groups in either the single-task training group, i.e., MotorTaskData_SingleTaskTrainingGroup.zip, or the dual-task training group, i.e., MotorTaskData_DualTaskTrainingGroup.zip. Each of the zip-files includes TESTING and TRAINING data in csv-files for each participant P separately. We further separated the TEMPLATE data and the PERFORMANCE data, i.e., for instance template test file of P1 corresponds with performance test file of P1. Each trial is presented in a row, where the header includes the segment information (i.e., first segment = 1, second segment = 2, and third segment = 3) for each data point. TEST data include trials with the practiced second segment and the catch trials with another second segment. TRAINING data include the 15 trials of the first and the last five training days (i.e., days 1 to 5, and days 18 to 22)

The impact of predictability on dual-task performance and implications for resource-sharing accounts.

The aim of this study was to examine the impact of predictability on dual-task performance by systematically manipulating predictability in either one of two tasks, as well as between tasks. According to capacity-sharing accounts of multitasking, assuming a general pool of resources two tasks can draw upon, predictability should reduce the need for resources and allow more resources to be used by the other task. However, it is currently not well understood what drives resource-allocation policy in dual tasks and which resource allocation policies participants pursue. We used a continuous tracking task together with an audiomotor task and manipulated advance visual information about the tracking path in the first experiment and a sound sequence in the second experiments (2a/b). Results show that performance predominantly improved in the predictable task but not in the unpredictable task, suggesting that participants did not invest more resources into the unpredictable task. One possible explanation was that the re-investment of resources into another task requires some relationship between the tasks. Therefore, in the third experiment, we covaried the two tasks by having sounds 250 ms before turning points in the tracking curve. This enabled participants to improve performance in both tasks, suggesting that resources were shared better between tasks

Additive effects of prior knowledge and predictive visual information in improving continuous tracking performance

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

Implicit and Explicit Knowledge Both Improve Dual Task Performance in a Continuous Pursuit Tracking Task

The goal of this study was to investigate the effect of predictability on dual-task performance in a continuous tracking task. Participants practiced either informed (explicit group) or uninformed (implicit group) about a repeated segment in the curves they had to track. In Experiment 1 participants practices the tracking task only, dual-task performance was assessed after by combining the tracking task with an auditory reaction time task. Results showed both groups learned equally well and tracking performance on a predictable segment in the dual-task condition was better than on random segments. However, reaction times did not benefit from a predictable tracking segment. To investigate the effect of learning under dual-task situation participants in Experiment 2 practiced the tracking task while simultaneously performing the auditory reaction time task. No learning of the repeated segment could be demonstrated for either group during the training blocks, in contrast to the test-block and retention test, where participants performed better on the repeated segment in both dual-task and single-task conditions. Only the explicit group improved from test-block to retention test. As in Experiment 1, reaction times while tracking a predictable segment were no better than reaction times while tracking a random segment. We concluded that predictability has a positive effect only on the predictable task itself possibly because of a task-shielding mechanism. For dual-task training there seems to be an initial negative effect of explicit instructions, possibly because of fatigue, but the advantage of explicit instructions was demonstrated in a retention test. This might be due to the explicit memory system informing or aiding the implicit memory system