Prescheduled Interleaving of Processing Reduces Interference in Motor-Cognitive Dual Tasks

Writing while walking: The impact of cognitive-motor multi-tasking on collision avoidance in human locomotion

BACKGROUND

When moving in public space, individuals are challenged with having to master multiple cognitive and motor demands, either simultaneously or in short succession. Empirical evidence suggests that cognitive-motor multi-tasking during walking may impact one or both, cognitive and motor performance. These performance changes may result from unintentional task-interference effects, but also from strategic behavioral changes to cope with the multiple task demands. Strategic changes in human walking behavior have been uncovered in experimental scenarios, in which individuals avoid colliding with other individuals or objects in the environment. However, whether collision avoidance behavior is sensitive to cognitive-motor multi-task demands has remained underexplored, yet. Thus, with this study, we aimed at systematically studying cognitive-motor multi-task effects on collision avoidance during human locomotion.

METHODS

Ten healthy participants (23.9 ± 4.3 years, 4 female) were walking at their preferred speed from a predefined start to end position under four experimental conditions: walking only (BL), walking while having to avoid a collision with another person (IO), writing a text message on a mobile phone while walking (cognitive-motor dual-task, DT), and writing while walking with collision avoidance demand (multi-task, MT). Parameters quantifying locomotor as well as collision avoidance behavior (path length, walking speed, minimum distance, path and speed adjustment) were assessed using optical motion tracking. In addition, performance in the writing task (errors, writing speed) was examined.

RESULTS

Participants' locomotor behavior was significantly affected by experimental conditions, with additive effects of multi-task demands on both path length (BL = DT < IO < MT) and walking speed (BL > IO > DT > MT). Further, participants showed an increased error rate and writing speed in the writing task when walking as compared to when standing still, independent of the presence of an interferer. Importantly, collision avoidance behavior was selectively influenced by cognitive-motor multi-task demands, with an increased minimum distance to the other person in the MT-condition, but no differences in path or speed adjustment.

DISCUSSION

Our results suggest significant multi-tasking effects of writing a message on the mobile phone while walking on both locomotor behavior and writing task performance. Collision avoidance behavior seems to be selectively affected by multi-task demands, reflected in an increased minimum passing distance, without overt changes in path or speed adjustments. This may be indicative for a strategic change in collision avoidance behavior towards a more cautious strategy to account for altered attention allocation and less visual feedback when writing while walking.

The self-organized task switching paradigm: Movement effort matters

The self-organized task switching paradigm enables to investigate the link between task performance and task selection in a voluntary task switching setting that benefits task switches over task repetitions. For example, waiting for a repetition-related stimulus onset denotes environmental costs, which are balanced with internal task-switch costs. Here we extent this research by asking whether movement effort also plays a crucial role for task selection. In detail, we investigate how motor-related consequences, i.e., increasing force for task repetitions, influence task-switching behavior. Participants voluntarily switched between a number (i.e., even or odd) or letter task (i.e., vowel or consonant) using a robot system for response execution. With consecutive task repetitions the robot system was harder to move to the response target as we systematically added a damping load. We found that switch rate correlated with cognitive switch costs (i.e., costs in: reaction time, r = -0.741, and error rate, r = -0.545), and motor repetition cost represented by movement-time increment, r = 0.414. Interestingly, switch rate also correlated with individual force maximum, r = -0.480. However, switch rate did not correlate with movement-impulse increment, r = -0.033. Stepwise multiple regression analyses across participants revealed that 66% of variance are explained including all predicting factors. Yet, only cognitive costs and individual force maximum reached significant importance in the regression model. Hence, we extended switch-rate analyses using linear regression on a within-subject level, and thus, keeping individual force maximum constant. We found about 84% of variance explained by motor and cognitive costs. Thereby, movement impulse predicted task selection more than reaction time and more than movement time. Thus, we demonstrated that both cognitive and motor consequences influence task-switch behavior. Furthermore, we showed that task selection is importantly modulated by motor effort related to individual motor skills.