Two sources of task prioritization: The interplay of effector-based and task order-based capacity allocation in the PRP paradigm

Abstract

When processing of two tasks overlaps, performance is known to suffer. In the well-established psychological refractory period (PRP) paradigm, tasks are triggered by two stimuli with a short temporal delay (stimulus onset asynchrony; SOA), thereby allowing control of the degree of task overlap. A decrease of the SOA reliably yields longer RTs of the task associated with the second stimulus (Task 2) while performance in the other task (Task 1) remains largely unaffected. This Task 2-specific SOA effect is usually interpreted in terms of central capacity limitations. Particularly, it has been assumed that response selection in Task 2 is delayed due to the allocation of less capacity until this process has been completed in Task 1. Recently, another important factor determining task prioritization has been proposed—namely, the particular effector systems associated with tasks. Here, we study both sources of task prioritization simultaneously by systematically combining three different effector systems (pairwise combinations of oculomotor, vocal, and manual responses) in the PRP paradigm. Specifically, we asked whether task order-based task prioritization (SOA effect) is modulated as a function of Task 2 effector system. The results indicate a modulation of SOA effects when the same (oculomotor) Task 1 is combined with a vocal versus a manual Task 2. This is incompatible with the assumption that SOA effects are solely determined by Task 1 response selection duration. Instead, they support the view that dual-task processing bottlenecks are resolved by establishing a capacity allocation scheme fed by multiple input factors, including attentional weights associated with particular effector systems.

Response-code conflict in dual-task interference and its modulation by age

“…We suggest that response-code conflicts between two concurrently implemented unimodal mapping rules entail outcome-related crosstalk that is flexibly modulated by a strategic prioritization of limited processing capacity and/or biased attention based on mapping selection difficulty as well as response grouping. Together with other recent studies (Hoffmann et al, 2020 ; Mattes et al, 2020 ; Schumacher & Hazeltine, 2016 ), our findings point to relevant mechanisms involved in dual-tasking that are not sufficiently captured by the structural response selection bottleneck model. Furthermore, they support the view that multiple mechanisms, including crosstalk between (sub)tasks and flexible resource allocation, jointly determine performance costs in dual-task settings, at least in those without entirely separate processing streams and with highly similar response sets.…”

Saccadic eye movements in dual tasking: No impairment of spatial planning, but delayed execution of saccades

“…Given the different temporal relations between planning and executing different motor responses with different effectors such as eyes, hands, and feet (see before), a more fine-grained picture of micro-dependencies between the different processes in dual tasks including a saccadic eye-movement task may emerge. In addition, this might shed further light on the issue of how assumptions about effector-based interference might add or substitute assumptions about central interference in dual-task situations (i.e., Hoffmann et al, 2020; Schubert et al, 2008, and others).…”

Brain functional characterization of response-code conflict in dual-tasking and its modulation by age

“…As mentioned earlier, dual-tasking implicates several cognitive processes (Worringer et al 2019) and shares variance with other subdomains of executive functioning (Himi et al 2019; Saylik et al 2022; Szameitat and Brunel Students 2022) to activate and maintain two task sets in parallel, control attentional processes and coordinate multiple actions. Furthermore, dual-task interference is affected by inter-individual differences and diverse contextual strategies to accomplish the tasks (Lehle and Hübner 2009; Hoffmann et al 2020). Therefore, studying the associations between dual-task brain activity and related cognitive domains can offer insights into characterizing the cognitive and neural mechanisms behind dual-task crosstalk and their age-related changes (Miyake et al 2000; Himi et al 2019; Saylik et al 2022) as well as the inter-individual differences and strategies implemented to cope with response-related dual-task crosstalk.…”