Scaling of the Parameters for Cost Balancing in Self- Organized Task Switching

Monno, Irina; Spitzer, Markus; Miller, Jeff; Dignath, David; Kiesel, Andrea · 2021 · Crossref

DOI: 10.5334/joc.137

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Summary

This study investigates the interplay between task performance costs and voluntary task selection in multitasking scenarios. While previous research established that switch costs (performance penalties) and switch rates are negatively correlated, this research specifically examines how the scaling of experimental parameters influences participants' ability to balance these costs. The authors utilized the self-organized task switching paradigm, where participants freely choose between two tasks (letter and number judgments) to optimize speed and accuracy. In this paradigm, the stimulus for a task repetition is delayed by an accumulating Stimulus Onset Asynchrony (SOA), creating a "waiting time" that increases with each consecutive repetition, whereas the switch stimulus is immediately available. The study aimed to identify which combination of SOA increments and Inter-Trial Intervals (ITIs) allows for the most efficient trade-off between waiting time and switch costs. The experiment employed a within-subject design with 118 participants. The researchers manipulated two factors: SOA increments (20 ms, 40 ms, and 60 ms) varied across sessions, and ITIs (0 ms, 250 ms, and 700 ms) varied blockwise to modulate switch costs. This created nine distinct conditions. Participants performed free-choice blocks where they decided which task to execute, with the goal of minimizing overall response time. Data analysis focused on median switch costs, switch rates, and the "switch SOA" (the waiting time at which a participant chose to switch). To assess the efficiency of cost balancing, the authors calculated a difference score between individual switch SOAs and switch costs, aiming to find conditions where this difference was minimal. Results indicated that both longer ITIs and larger SOA increments significantly increased switch rates. Switch costs decreased as ITIs lengthened, ranging from approximately 154 ms at 0 ms ITI to 38 ms at 700 ms ITI. Crucially, the study found that participants balanced their switch costs and waiting times most effectively in conditions with medium switch costs (ITI 250 ms) and small SOA increments (20 ms). In these settings, the difference between switch SOA and switch costs was smallest and statistically non-significant, suggesting optimal adaptation. Small SOA increments allowed for finer-grained adjustments in switching behavior compared to larger increments. Additionally, strong negative correlations were observed between individual switch costs and switch rates across all conditions, reinforcing the link between performance costs and selection behavior. The findings demonstrate that voluntary task switching is driven by a strategic cost-benefit arbitration, where participants adjust their switching behavior to minimize the sum of switch costs and waiting times. The study highlights that the granularity of the waiting time manipulation (SOA increment) is critical for enabling precise adaptation; smaller increments facilitate better balancing. These results support theoretical models suggesting that cognitive control in multitasking involves utility-based decisions that weigh performance costs against temporal delays. By identifying the parameters that maximize efficient cost balancing, the research provides insights into the mechanisms of voluntary cognitive control and offers methodological guidance for future studies on multitasking and decision-making.

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• task switching