Evidence map›Paper›PMID 36227284›Full record

ArticlePsychological review2023

Linking computational models of two core tasks of cognitive control.

Maria M Robinson, Mark Steyvers

Abstract read
In one paragraph

Article in Psychological review, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Review
  9. Cognitive Control.Annual review of psychology · 2025
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Maria M RobinsonDepartment of Psychology, University of California, San Diego.ORCID 0000-0002-9797-4068
Mark SteyversDepartment of Cognitive Sciences, University of California, Irvine.ORCID 0000-0003-1466-5647

Funding

Modeling Correlated Signals in Memory SystemsF32MH127823 · NIMH · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI ROBINSON, MARIA · 2021 to 2023
$181k
NIMH NIH HHS F32 MH127823
6 · The paper itself

Abstract

Cognitive control refers to the ability to maintain goal-relevant information in the face of distraction, making it a core construct for understanding human thought and behavior. There is great theoretical and practical value in building theories that can be used to explain or to predict variations in cognitive control as a function of experimental manipulations or individual differences. A critical step toward building such theories is determining which latent constructs are shared between laboratory tasks that are designed to measure cognitive control. In the current work, we examine this question in a novel way by formally linking computational models of two canonical cognitive control tasks, the Eriksen flanker and task-switching task. Specifically, we examine whether model parameters that capture cognitive control processes in one task can be swapped across models to make predictions about individual differences in performance on another task. We apply our modeling and analysis to a large scale data set from an online cognitive training platform, which optimizes our ability to detect individual differences in the data. Our results suggest that the flanker and task-switching tasks probe common control processes. This finding supports the view that higher level cognitive control processes as opposed to solely strategies in speed and accuracy tradeoffs, or perceptual processing and motor response speed are shared across the two tasks. We discuss how our computational modeling substitution approach addresses limitations of prior efforts to relate performance across different cognitive control tasks, and how our findings inform current theories of cognitive control. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Indexed as

CognitionIndividualityComputer SimulationHumansReaction Time

Identifiers

PMID36227284
PMCPMC10257386

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Registered trials

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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.