Cognitive control and capacity for prospective memory in complex dynamic environments.
DOI: 10.1037/xge0000599
archive: archived pipeline: cataloged verified
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Summary
This study investigates how cognitive control and attentional capacity support prospective memory (PM) in complex, dynamic environments, addressing a gap in literature that has primarily relied on simple laboratory tasks. The authors aim to determine whether the reliance on cognitive control mechanisms observed in basic PM tasks persists when ongoing tasks are highly demanding and subject to time pressure, or if capacity sharing becomes the dominant factor. To test this, the researchers applied the Prospective Memory Decision Control (PMDC) model, an evidence accumulation framework, to data from a simulated air traffic control conflict detection task. Participants performed an ongoing task of detecting potential aircraft conflicts while concurrently monitoring for specific PM targets (aircraft callsigns with repeated letters). The experimental design included manipulations of PM load and time pressure, achieved by varying trial loads and response deadlines, to assess how resource allocation and control strategies adapt under different demands. The PMDC model was fitted to response time and accuracy data to quantify latent cognitive processes, including proactive control (threshold adjustments), reactive control (inhibition/excitation of accumulation rates), and capacity sharing (accumulation rates reflecting resource availability). The results indicated that PM demands encouraged proactive control, where participants raised decision thresholds for the ongoing task to prioritize PM accuracy. However, this proactive control was reduced under high time pressure to facilitate faster responding. Reactive inhibitory control was observed when PM targets were encountered, slowing ongoing task processing. Crucially, the study found that both time pressure and PM load increased the total amount of cognitive resources available. However, as demands exceeded the system's capacity limit, resources were reallocated between tasks. Specifically, increased time pressure caused the ongoing task to consume more resources, thereby draining resources available for PM processing. The significance of these findings lies in providing the first detailed quantitative understanding of how attentional resources and cognitive control mechanisms interact in complex dynamic environments. The study demonstrates that while cognitive control is critical for managing PM, it is not the sole mechanism; capacity sharing becomes evident when task demands exceed cognitive limits. This challenges previous assumptions derived from simple laboratory paradigms that PM costs are purely due to control strategies rather than resource competition. The results imply that in high-stakes professions like air traffic control, performance errors may arise not just from strategic failures but from the physical limits of cognitive capacity when multiple high-demand tasks compete for resources.
Key finding
In complex dynamic environments, prospective memory relies on cognitive control mechanisms that trade off with resource allocation, where high time pressure forces a reallocation of cognitive resources from prospective memory tasks to ongoing tasks to maintain performance speed.
Methodology
simulator
Sample size: 47
Provenance
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | author_sweep | — | — | 3 | 2026-05-28 |
| archive | success | canonical_url | — | — | 11 | 2026-06-06 |
| extract | success | cached | — | — | 3 | 2026-06-10 |
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| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-04 |
| enrich | success | — | — | — | 1 | 2026-05-28 |
| promote | success | — | — | — | 1 | 2026-06-04 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 2 | 2026-06-10 |
| tag | success | vector_similarity | — | — | 15 | 2026-06-11 |
| verify | success | — | — | — | 2 | 2026-06-10 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.
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