Evidence map›Paper›PMID 35015871›Full record

ArticleJournal of cognitive neuroscience2022

Neural Dynamics of Context-sensitive Adjustments in Cognitive Flexibility.

Audrey Siqi-Liu, Tobias Egner, Marty G Woldorff

Abstract read
In one paragraph

Article in Journal of cognitive neuroscience, 2022. 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. Review
  4. Article
  5. Article
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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

3 authors.

Audrey Siqi-LiuDuke University, Durham, NC.
Tobias EgnerDuke University, Durham, NC.
Marty G WoldorffDuke University, Durham, NC.

Funding

Neural Mechanisms of Cognitive Meta-FlexibilityR01MH116967 · NIMH · DUKE UNIVERSITY · PI EGNER, TOBIAS · 2019 to 2023
$2.0M
NIMH NIH HHS R01 MH116967
6 · The paper itself

Abstract

To adaptively interact with the uncertainties of daily life, we must match our level of cognitive flexibility to situations that place different demands on our ability to focus on the current task while remaining sensitive to cues that signal other, more urgent tasks. Such cognitive-flexibility adjustments in response to changing contextual demands (metaflexibility) have been observed in cued task-switching paradigms, where the performance cost incurred by switching versus repeating tasks (switch cost) scales inversely with the proportion of switches (PS) within a block of trials. However, the neural underpinnings of these adjustments in cognitive flexibility are not well understood. Here, we recorded 64-channel EEG measures of electrical brain activity as participants switched between letter and digit categorization tasks in varying PS contexts, from which we extracted ERPs elicited by the task cue and EEG alpha-power differences during both the cue-to-target interval and the resting precue period. The temporal resolution of EEG/ERPs allowed us to test whether contextual adjustments in cognitive flexibility are mediated by tonic changes in processing mode, or by changes in phasic, task-cue-triggered processes. We observed reliable modulation of behavioral switch cost by PS context that were mirrored in both cue-evoked ERP and time-frequency effects, but not in blockwide precue EEG changes. These results indicate that different levels of cognitive flexibility are instantiated in response to the presentation of task cues, rather than by being maintained as a tonic neural-activity state difference between low- and high-switch contexts.

Indexed as

CognitionCuesPsychomotor PerformanceElectroencephalographyEvoked PotentialsHumansReaction Time

Identifiers

PMID35015871
PMCPMC9403815

What OpenQuestion holds

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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.