Evidence map›Paper›PMID 35022456›Full record

ArticleScientific reports2022

Recruitment of a long-term memory supporting neural network during repeated maintenance of a multi-item abstract visual image in working memory.

Klaartje T H Heinen, J Leon Kenemans, Stefan van der Stigchel

Abstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Klaartje T H HeinenExperimental Psychology, Utrecht University, Heidelberglaan 1, 3584 CS, Utrecht, The Netherlands. Kheinen@gmail.com.
J Leon KenemansExperimental Psychology, Utrecht University, Heidelberglaan 1, 3584 CS, Utrecht, The Netherlands.
Stefan van der StigchelExperimental Psychology, Utrecht University, Heidelberglaan 1, 3584 CS, Utrecht, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Humans can flexibly transfer information between different memory systems. Information in visual working memory (VWM) can for instance be stored in long-term memory (LTM). Conversely, information can be retrieved from LTM and temporarily held in WM when needed. It has previously been suggested that a neural transition from parietal- to midfrontal activity during repeated visual search reflects transfer of information from WM to LTM. Whether this neural transition indeed reflects consolidation and is also observed when memorizing a rich visual scene (rather than responding to a single target), is not known. To investigate this, we employed an EEG paradigm, in which abstract six-item colour-arrays were repeatedly memorized and explicitly visualized, or merely attended to. Importantly, we tested the functional significance of a potential neural shift for longer-term consolidation in a subsequent recognition task. Our results show a gradually enhanced- and sustained modulation of the midfrontal P170 component and a decline in parietal CDA, during repeated WM maintenance. Improved recollection/visualization of memoranda upon WM-cueing, was associated with contralateral parietal- and right temporal activity. Importantly, only colour-arrays previously held in WM, induced a greater midfrontal P170-response, together with left temporal- and late centro-parietal activity, upon re-exposure. These findings provide evidence for recruitment of an LTM-supporting neural network which facilitates visual WM maintenance.

Indexed as

Nerve NetRecruitment, NeurophysiologicalAdultElectroencephalographyFemaleHealthy VolunteersHumansMaleMemory ConsolidationMemory, Short-TermVisual PerceptionYoung Adult

Identifiers

PMID35022456
PMCPMC8755800

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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.