Evidence map›Paper›PMID 40800981›Full record

ArticleImaging neuroscience (Cambridge, Mass.)2025

Dynamic network features of functional and structural brain networks support visual working memory in aging adults.

Josh Neudorf, Kelly Shen, Anthony R McIntosh

Abstract read
In one paragraph

Article in Imaging neuroscience (Cambridge, Mass.), 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. Article
  2. 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.

Josh NeudorfInstitute for Neuroscience and Neurotechnology, Simon Fraser University, Burnaby, Canada.ORCID https://orcid.org/0000-0001-9227-1358
Kelly ShenInstitute for Neuroscience and Neurotechnology, Simon Fraser University, Burnaby, Canada.
Anthony R McIntoshInstitute for Neuroscience and Neurotechnology, Simon Fraser University, Burnaby, Canada.ORCID https://orcid.org/0000-0002-1784-5662

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this work, we investigated how the relationship between structural connectivity and the dynamics of functional connectivity changes with age to benefit cognitive ability. Visual working memory (VWM) is an important brain function that allows us to maintain a mental representation of the world around us, but its capacity and precision peak by around 20 years old and decrease steadily throughout the rest of our lives. This research examined the functional brain network dynamics associated with VWM throughout the lifespan and found that Default Mode Network and Fronto-Parietal Network states were more well represented in individuals with better VWM. Furthermore, transitions from the Visual/Somatomotor Network state to the Attention Network state were more well represented in older adults, and a network control theory simulation demonstrated that structural connectivity differences supporting this transition were associated with better VWM, especially in middle-aged individuals. The structural connectivity of regions from all states was important for supporting this transition in younger adults, while regions within the Visual/Somatomotor and Attention Network states were more important in older adults. These findings demonstrate that structural connectivity supports flexible, functional dynamics that allow for better VWM with age and may lead to important interventions to uphold healthy VWM throughout the lifespan.

Indexed as

diffusion-weighted magnetic resonance imagingdynamic functional connectivityhealthy agingnetwork control theoryresting-state functional magnetic resonance imagingvisual working memory

Identifiers

PMID40800981
PMCPMC12319731

What OpenQuestion holds

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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.