ArticleBrain sciences2021
Cognitive Control of Working Memory: A Model-Based Approach.
Article in Brain sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- A diffusion model analysis of task set inertia and task set reconfiguration in ADHD.Journal of the International Neuropsychological Society : JINS · 2026Article
- Article
- Psychometrics of drift-diffusion model parameters derived from the Eriksen flanker task: Reliability and validity in two independent samples.Cognitive, affective & behavioral neuroscience · 2025Article
- Self-prioritization in working memory gating.Attention, perception & psychophysics · 2025Article
- Integrating the dual-system theory in motor: dynamic framework construction for motor decision-making.Frontiers in psychology · 2025Article
- The Brain's Topographical Organization Shapes Dynamic Interaction Patterns That Support Flexible Behavior Based on Rules and Long-Term Knowledge.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024Article
- Wagers for work: Decomposing the costs of cognitive effort.PLoS computational biology · 2024Article
- Joint Modelling of Latent Cognitive Mechanisms Shared Across Decision-Making Domains.Computational brain & behavior · 2024Article
- Beyond Reactive Inhibition: Unpacking the Multifaceted Nature of Motor Inhibition.Brain sciences · 2023Article
- Task Switching: On the Relation of Cognitive Flexibility with Cognitive Capacity.Journal of Intelligence · 2023Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Working memory (WM)-based decision making depends on a number of cognitive control processes that control the flow of information into and out of WM and ensure that only relevant information is held active in WM's limited-capacity store. Although necessary for successful decision making, recent work has shown that these control processes impose performance costs on both the speed and accuracy of WM-based decisions. Using the reference-back task as a benchmark measure of WM control, we conducted evidence accumulation modeling to test several competing explanations for six benchmark empirical performance costs. Costs were driven by a combination of processes, running outside of the decision stage (longer non-decision time) and showing the inhibition of the prepotent response (lower drift rates) in trials requiring WM control. Individuals also set more cautious response thresholds when expecting to update WM with new information versus maintain existing information. We discuss the promise of this approach for understanding cognitive control in WM-based decision making.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.