Evidence map›Paper›PMID 39906991›Full record

ArticleThe European journal of neuroscience2025

Network Segregation and Integration Changes in Healthy Aging: Evidence From EEG Subbands During the Visual Short-Term Memory Binding Task.

Ezgi Fide, Emre Bora, Görsev Yener

Abstract read
In one paragraph

Article in The European journal of neuroscience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Converging on control: Rethinking treatment-resistant depression through network neuroscience.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2026
    Article
  2. Review
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.

Ezgi FideDepartment of Psychology, Faculty of Health, York University, Toronto, Ontario, Canada.ORCID 0000-0002-7837-3996
Emre BoraDepartment of Neurosciences, Institute of Health Sciences, Dokuz Eylül University, Izmir, Turkey.ORCID 0000-0002-1598-6832
Görsev YenerDepartment of Neurosciences, Institute of Health Sciences, Dokuz Eylül University, Izmir, Turkey.ORCID 0000-0002-7756-4387

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Working memory, which tends to be the most vulnerable cognitive domain to aging, is thought to depend on a functional brain network for efficient communication. The dynamic communication within this network is represented by segregation and integration. This study aimed to investigate healthy aging by examining age effect on outcomes of graph theory analysis during the visual short-term memory binding (VSTMB) task. VSTMB tasks rely on the integration of visual features and are less sensitive to semantic and verbal strategies. Effects of age on neuropsychological test scores, along with the EEG graph-theoretical integration, segregation and global organization metrics in frequencies from delta to gamma band were investigated. Neuropsychological assessment showed low sensitivity as a measure of age-related changes. EEG results indicated that network architecture changed more effectively during middle age, while this effectiveness appears to vanish or show compensatory mechanisms in the elderly. These differences were further found to be related to cognitive domain scores. This study is the first to demonstrate differences in working memory network architecture across a broad age range.

Indexed as

AgingBrainHealthy AgingMemory, Short-TermNerve NetVisual PerceptionAdultAgedAged, 80 and overElectroencephalographyFemaleHumansMaleMiddle AgedNeuropsychological TestsYoung Adultaginggraph theory analysisintegrationsegregationSWworking memory

Identifiers

PMID39906991
PMCPMC11795350

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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.