Evidence map›Paper›PMID 41790939›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2026

Reverse engineering what makes a symbol memorable.

Brady R T Roberts, Wilma A Bainbridge

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Brady R T RobertsDepartment of Psychology, University of Chicago, Chicago, IL 60637.ORCID 0000-0002-2228-8805
Wilma A BainbridgeDepartment of Psychology, University of Chicago, Chicago, IL 60637.ORCID 0000-0002-7554-0736

Funding

The neural and behavioral causes underlying differences between visual perception and memoryR01EY034432 · NEI · UNIVERSITY OF CHICAGO · PI Wilma A. Bainbridge · 2023 to 2026
$1.6M
HHS | NIH | National Eye Institute (NEI) R01-EY034432Natural Sciences and Engineering Research Council of Canada (NSERC) Postdoctoral FellowshipNEI NIH HHS R01 EY034432
6 · The paper itself

Abstract

Symbols may represent the first form of human visual communication, yet little is known about the cognitive and neural mechanisms supporting memory for these pervasive graphics. By investigating memory for everyday symbols, we can understand how abstract concepts are concretized with simple referents and later processed in visual memory systems. Recently, symbols have been found to be highly memorable, especially relative to words, but it remains unclear what drives their heightened memorability. We identified the key visual and conceptual attributes driving high memorability for symbols. Participants were tested on their memory for conventional symbols (e.g., !@#$%) before sorting them based on visual or conceptual features. Principal component analyses performed on the sorting data revealed which of these features predict memory for symbols. Generative AI was then used to accentuate or downplay these predictive features to create a set of memorable and forgettable novel symbols. A memory test revealed that symbols designed to be memorable were not only better recognized than those designed to be forgettable, but they also afforded superior recall of associated abstract words. This work demonstrates that certain stimulus features drive memory for images beyond distinctiveness or context and offers clear evidence that memory can be intentionally engineered.

Indexed as

MemoryGenerative Artificial IntelligenceHumansMental RecallPrincipal Component AnalysisSymbolismAI image generationcued recallmemorabilityrecognition memorysymbols

Identifiers

PMID41790939
PMCPMC12974420

What OpenQuestion holds

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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.