Trends in Cognitive Sciences
Volume 23, Issue 9, September 2019, Pages 769-783
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Review
Measuring Adaptive Control in Conflict Tasks

https://doi.org/10.1016/j.tics.2019.07.002Get rights and content

Highlights

  • Early putative indices of adaptive control in conflict tasks have spurred not only a great deal of research but also numerous discussions on what these indices actually measure.

  • Recent studies have shown that adaptive control effects can be observed after controlling for low-level confounds. However, many canonical findings in the literature, for instance concerning the functional neuroanatomy of adaptive control, are based on older, confounded designs, and may thus be subject to revision.

  • This research field is now starting to experience a second wave of studies on adaptive control in conflict tasks employing improved designs that allow us to (re)address old and new questions.

The past two decades have witnessed an explosion of interest in the cognitive and neural mechanisms of adaptive control processes that operate in selective attention tasks. This has spawned not only a large empirical literature and several theories but also the recurring identification of potential confounds and corresponding adjustments in task design to create confound-minimized metrics of adaptive control. The resulting complexity of this literature can be difficult to navigate for new researchers entering the field, leading to suboptimal study designs. To remediate this problem, we present here a consensus view among opposing theorists that specifies how researchers can measure four hallmark indices of adaptive control (the congruency sequence effect, and list-wide, context-specific, and item-specific proportion congruency effects) while minimizing easy-to-overlook confounds.

Section snippets

The Quest for Pure Measures of Adaptive Control

Cognitive control (see Glossary) allows people to act in ways that are consistent with their internal goals [1]. To investigate such control, psychologists often use selective attention tasks that create conflict by pitting instructed task goals against incompatible stimulus information and automatic action tendencies (i.e., conflict tasks). For example, in the seminal Stroop task [2], researchers study how the ability to identify the color of a printed word varies with whether the word cues a

The Need for 'Inducer' and 'Diagnostic' Items when Studying Adaptive Control

When employing conflict tasks, the goal of the researcher is typically to isolate changes in behavior that reflect adjustments to relatively abstract attentional settings or task representations (e.g., ‘pay more attention to the target’ or ‘be cautious in selecting the response’) as opposed to concrete settings (e.g., ‘look at the green square’ or ‘press the left response key’). For example, in the Stroop task, abstract adjustments of control could involve paying more attention to the

The Congruency Sequence Effect

The CSE, sometimes referred to as the ‘Gratton effect’ [28] or ‘conflict adaptation effect’ [6], describes the finding that the congruency effect is reduced following incongruent versus congruent trials (27., 29. for review). The CSE is thought to measure adaptive control on a trial-by-trial basis (Box 2). However, over a decade ago researchers noted that, in typical two-alternative forced choice (2-AFC) conflict tasks with small stimulus sets, the nature of stimulus or response repetitions

The List-Wide Proportion Congruency Effect

The LWPCE describes the finding of a smaller congruency effect in blocks of more- relative to less-frequent incongruent trials. The LWPCE is thought to measure global adaptations of control by the likelihood of experiencing conflict (high or low) in a particular block (list) of trials ([48] for a user’s guide to the proportion congruency manipulation). In many earlier studies, however, the frequency of incongruent trials was confounded with the frequency with which specific stimuli appeared.

The Context-Specific Proportion Congruency Effect

The CSPCE refers to the observation that the congruency effect can change when proportion congruency is manipulated across two or more contexts that vary on a trial-by-trial basis. For instance, presenting a higher proportion of incongruent stimuli in one of two possible stimulus locations can lead to smaller congruency effects at that location than at the other location. Unlike the LWPCE, the CSPCE is thought to index adaptations to different congruency proportions within a block which are

The Item-Specific Proportion Congruency Effect

Our final index of adaptive control is the ISPCE, which refers to the finding that the size of the congruency effect for a particular item varies with how frequently it appears in incongruent versus congruent trials. For example, the congruency effect is smaller for target items that appear more frequently with incongruent distractors than for target items that appear more frequently with congruent distractors. Much like the LWPCE and the CSPCE, the ISPCE reflects adaptations to different

Power Analysis and Design Planning

Our recommendation to use inducer and diagnostic items for measuring adaptive control also comes with a warning regarding statistical power. The CSE, LWPCE, ISPCE, and CSPCE are all calculated as the difference between two congruency effects, which are themselves difference scores. Taking a difference between difference scores can increase variability [76]. Hence, if a design has sufficient power to measure a congruency effect, it might not necessarily have sufficient power to measure a

When Low-Level Learning Is Not a 'Confound'

We recommend that researchers employ diagnostic items as a means to measure adaptive control because effects on these items are not easily explained by simple response-repetition effects or the formation of stimulus–response (or stimulus–stimulus) associations. Therefore, they license consideration of adaptive control accounts. This also led us to label as 'confounds' design features that allow these lower-level associative effects to influence performance, consistent with the decades-old

Concluding Remarks

The current literature on adaptive control is characterized by a wide heterogeneity of paradigms and designs. Thus, for researchers who are not ‘in the weeds’ of this field, it can be difficult to infer a consensus view on the steps that are necessary to optimally study adaptive control in conflict tasks. We argue here that there is one key consideration. Specifically, to measure the hypothetical effects of adaptive control, researchers should employ diagnostic stimuli (and associated

Acknowledgments

We would like to thank Luis Jiménez, Juan Lupiáñez, and three anonymous reviewers for useful suggestions on an earlier version of this manuscript, as well as Frederick Verbruggen for inspiration for this project. J.M.B. was supported by the National Institute On Aging of the National Institutes of Health under award number R21AG057937, J.R.S. was supported by the Programme d’Investissements d’Avenir (project ISITE-BFC) under award number ANR15-IDEX-0003, and T.E. was supported in part by the

Glossary

Adaptive control
refers here to control processes or executive functions that dynamically adjust processing selectivity in response to changes in the environment or to internal (performance) monitoring signals (e.g., conflicts).
Cognitive control
the term (also 'executive functions') is generally used to describe a set of (not always well-defined) higher-order processes that are thought to direct, correct, and redirect behavior in line with internal goals and current context.
(Cognitive) Conflict

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