Evidence map›Paper›PMID 26884228›Full record

ArticleLearning & memory (Cold Spring Harbor, N.Y.)2016

Chunking improves symbolic sequence processing and relies on working memory gating mechanisms.

Oleg Solopchuk, Andrea Alamia, Etienne Olivier, Alexandre Zénon

Abstract read
In one paragraph

Article in Learning & memory (Cold Spring Harbor, N.Y.), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Computational insights on asymmetricalCognitive neurodynamics · 2024
    Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Short-term memory for spatial, sequential and duration information.Current opinion in behavioral sciences · 2017
    Review
  8. Non-parametric Algorithm to Isolate Chunks in Response Sequences.Frontiers in behavioral neuroscience · 2016
    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.

Oleg SolopchukInstitute of Neuroscience, Université catholique de Louvain, 1200 Brussels, Belgium.
Andrea AlamiaInstitute of Neuroscience, Université catholique de Louvain, 1200 Brussels, Belgium.
Etienne OlivierInstitute of Neuroscience, Université catholique de Louvain, 1200 Brussels, Belgium.
Alexandre ZénonInstitute of Neuroscience, Université catholique de Louvain, 1200 Brussels, Belgium alexandre.zenon@uclouvain.be.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chunking, namely the grouping of sequence elements in clusters, is ubiquitous during sequence processing, but its impact on performance remains debated. Here, we found that participants who adopted a consistent chunking strategy during symbolic sequence learning showed a greater improvement of their performance and a larger decrease in cognitive workload over time. Stronger reliance on chunking was also associated with higher scores in a WM updating task, suggesting the contribution of WM gating mechanisms to sequence chunking. Altogether, these results indicate that chunking is a cost-saving strategy that enhances effectiveness of symbolic sequence learning.

Indexed as

LearningMemory, Short-TermAdultFemaleHumansMalePsychomotor PerformancePupilReaction TimeYoung Adult

Identifiers

PMID26884228
PMCPMC4755266

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

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.