Evidence map›Paper›PMID 37239283›Full record

ArticleBrain sciences2023

Semantic Bimodal Presentation Differentially Slows Working Memory Retrieval.

Jia Cheng, Jingjing Li, Aijun Wang, Ming Zhang

Abstract read
In one paragraph

Article in Brain sciences, 2023. 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

4 authors.

Jia ChengDepartment of Psychology, Research Center for Psychology and Behavioral Sciences, Soochow University, Suzhou 215123, China.ORCID 0009-0002-5208-4886
Jingjing LiDepartment of Psychology, Research Center for Psychology and Behavioral Sciences, Soochow University, Suzhou 215123, China.
Aijun WangDepartment of Psychology, Research Center for Psychology and Behavioral Sciences, Soochow University, Suzhou 215123, China.ORCID 0000-0003-4981-3400
Ming ZhangDepartment of Psychology, Suzhou University of Science and Technology, Suzhou 215009, China.

Funding

Japan Society for the Promotion of Science 20K04381
6 · The paper itself

Abstract

Although evidence has shown that working memory (WM) can be differentially affected by the multisensory congruency of different visual and auditory stimuli, it remains unclear whether different multisensory congruency about concrete and abstract words could impact further WM retrieval. By manipulating the attention focus toward different matching conditions of visual and auditory word characteristics in a 2-back paradigm, the present study revealed that for the characteristically incongruent condition under the auditory retrieval condition, the response to abstract words was faster than that to concrete words, indicating that auditory abstract words are not affected by visual representation, while auditory concrete words are. Alternatively, for concrete words under the visual retrieval condition, WM retrieval was faster in the characteristically incongruent condition than in the characteristically congruent condition, indicating that visual representation formed by auditory concrete words may interfere with WM retrieval of visual concrete words. The present findings demonstrated that concrete words in multisensory conditions may be too aggressively encoded with other visual representations, which would inadvertently slow WM retrieval. However, abstract words seem to suppress interference better, showing better WM performance than concrete words in the multisensory condition.

Indexed as

abstract wordsbimodal n-backconcrete wordsmodal representationsmultisensory congruencyworking memory

Identifiers

PMID37239283
PMCPMC10216103

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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.