Evidence map›Paper›PMID 29952621›Full record

ArticlePsychological review2018

Chunking as a rational strategy for lossy data compression in visual working memory.

Matthew R Nassar, Julie C Helmers, Michael J Frank

Abstract read
In one paragraph

Article in Psychological review, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.

0numbers the graph read from it
0cells of the map it votes in
52citing 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

52 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Skill Memory Expansion Shapes Micro-Scale Dynamics of Skill Learning.bioRxiv : the preprint server for biology · 2026
    Article
  5. Article
  6. A population vector model of visual working memory for real-world scenes.Journal of experimental psychology. General · 2026
    Article
  7. A Population Vector Model of Visual Working Memory for Real-World Scenes.bioRxiv : the preprint server for biology · 2026
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. The Role of Event Number and Duration in Time-Compressed Memory Replay.Open mind : discoveries in cognitive science · 2025
    Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. 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

3 authors.

Matthew R NassarDepartment of Cognitive, Linguistic, and Psychological Sciences, Brown Institute for Brain Science, Brown University.ORCID 0000-0002-5397-535X
Julie C HelmersDepartment of Cognitive, Linguistic, and Psychological Sciences, Brown Institute for Brain Science, Brown University.
Michael J FrankDepartment of Cognitive, Linguistic, and Psychological Sciences, Brown Institute for Brain Science, Brown University.

Funding

Clinical and Computational Studies of Dopamine Function in SchizophreniaR01MH080066 · NIMH · UNIVERSITY OF MARYLAND BALTIMORE · PI GOLD, JAMES M. · 2008 to 2017
$6.4M
Brain Science Computer ClusterS10OD016366 · OD · BROWN UNIVERSITY · PI DONOGHUE, JOHN P · 2013 to 2013
$600k
Cognitive and Molecular Challenges to Statistical Inference Across Healthy Aging.K99AG054732 · NIA · BROWN UNIVERSITY · PI NASSAR, MATTHEW · 2017 to 2018
$223k
Does prefrontal dopamine modulate error signals to optimally adjust learning?F32MH102009 · NIMH · BROWN UNIVERSITY · PI NASSAR, MATTHEW · 2014 to 2016
$134k
National Science FoundationNIA NIH HHS K99 AG054732NIH HHS S10 OD016366NIMH NIH HHS F32 MH102009NIMH NIH HHS R01 MH080066
6 · The paper itself

Abstract

The nature of capacity limits for visual working memory has been the subject of an intense debate that has relied on models that assume items are encoded independently. Here we propose that instead, similar features are jointly encoded through a "chunking" process to optimize performance on visual working memory tasks. We show that such chunking can: (a) facilitate performance improvements for abstract capacity-limited systems, (b) be optimized through reinforcement, (c) be implemented by center-surround dynamics, and (d) increase effective storage capacity at the expense of recall precision. Human performance on a variant of a canonical working memory task demonstrated performance advantages, precision detriments, interitem dependencies, and trial-to-trial behavioral adjustments diagnostic of performance optimization through center-surround chunking. Models incorporating center-surround chunking provided a better quantitative description of human performance in our study as well as in a meta-analytic dataset, and apparent differences in working memory capacity across individuals were attributable to individual differences in the implementation of chunking. Our results reveal a normative rationale for center-surround connectivity in working memory circuitry, call for reevaluation of memory performance differences that have previously been attributed to differences in capacity, and support a more nuanced view of visual working memory capacity limitations: strategic tradeoff between storage capacity and memory precision through chunking contribute to flexible capacity limitations that include both discrete and continuous aspects. (PsycINFO Database Record

Indexed as

IndividualityInformation TheoryModels, TheoreticalReinforcement, PsychologyHumansMemory, Short-TermVisual Perception

Identifiers

PMID29952621
PMCPMC6026019

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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.