Evidence map›Paper›PMID 37152832›Full record

ArticleJournal of cognition2023

Proactively Adjusting Stopping: Response Inhibition is Faster when Stopping Occurs Frequently.

Roos A Doekemeijer, Anneleen Dewulf, Frederick Verbruggen, C Nico Boehler

Abstract read
In one paragraph

Article in Journal of cognition, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Does the stop-signal P3 reflect inhibitory control?Cortex; a journal devoted to the study of the nervous system and behavior · 2025
    Review
  5. Article
  6. Article
  7. Article
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

4 authors.

Roos A DoekemeijerGhent University, Ghent, Belgium.ORCID https://orcid.org/0000-0002-5670-2971
Anneleen DewulfGhent University, Ghent, Belgium.ORCID https://orcid.org/0000-0003-4215-0421
Frederick VerbruggenGhent University, Ghent, Belgium.ORCID https://orcid.org/0000-0002-7958-0719
C Nico BoehlerGhent University, Ghent, Belgium.ORCID https://orcid.org/0000-0001-5963-2780

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

People are able to stop actions before they are executed, and proactively slow down the speed of going in line with their expectations of needing to stop. Such slowing generally increases the probability that stopping will be successful. Surprisingly though, no study has clearly demonstrated that the speed of stopping (measured as the stop-signal reaction time, SSRT) is reduced by such proactive adjustments. In addition to a number of studies showing non-significant effects, the only study that initially had observed a clear effect in this direction found that it was artifactually driven by a confounding variable (specifically, by context-independence violations, which jeopardize the validity of the SSRT estimation). Here, we tested in two well-powered and well-controlled experiments whether the SSRT is shorter when stopping is anticipated. In each experiment, we used a Stop-Signal Task, in which the stop-trial frequency was either high (50%) or low (20%). Our results robustly show that the SSRT was shorter when stop signals were more anticipated (i.e., in the high-frequent condition) while carefully controlling for context-independence violations. Hence, our study is first to demonstrate a clear proactive benefit on the speed of stopping, in line with an ability to emphasize going or stopping, by trading off the speed of both.

Indexed as

proactive adjustmentsproactive inhibitory controlresponse inhibitionSSRTstop-trial frequency

Identifiers

PMID37152832
PMCPMC10162359

What OpenQuestion holds

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LicenceCC BY
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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.