Evidence map›Paper›PMID 34074762›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2021

Segregation, integration, and balance of large-scale resting brain networks configure different cognitive abilities.

Rong Wang, Mianxin Liu, Xinhong Cheng, Ying Wu, Andrea Hildebrandt, Changsong Zhou

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 141 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
141citing papers in PubMed, 2 pooled it
–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

141 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Impact of Different Types of Sedentary Behaviour on Cognitive Function in Older Adults: A Systematic Review.Health promotion journal of Australia : official journal of Australian Association of Health Promotion Professionals · 2026
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81 more citing papers are in PubMed but not listed here.

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

6 authors.

Rong WangCollege of Science, Xi'an University of Science and Technology, Xi'an 710054, China.ORCID 0000-0001-8599-9850
Mianxin LiuDepartment of Physics, Centre for Nonlinear Studies, Beijing-Hong Kong-Singapore Joint Centre for Nonlinear and Complex Systems (Hong Kong), Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Hong Kong.
Xinhong ChengCollege of Science, Xi'an University of Science and Technology, Xi'an 710054, China.
Ying WuSchool of Aerospace Engineering, Xi'an Jiaotong University, Xi'an 710049, China.
Andrea HildebrandtDepartment of Psychology, Carl von Ossietzky Universität Oldenburg, 26129 Oldenburg, Germany; cszhou@hkbu.edu.hk andrea.hildebrandt@uni-oldenburg.de.ORCID 0000-0001-5564-0126
Changsong ZhouDepartment of Physics, Centre for Nonlinear Studies, Beijing-Hong Kong-Singapore Joint Centre for Nonlinear and Complex Systems (Hong Kong), Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Hong Kong; cszhou@hkbu.edu.hk andrea.hildebrandt@uni-oldenburg.de.ORCID 0000-0002-4130-0216

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diverse cognitive processes set different demands on locally segregated and globally integrated brain activity. However, it remains an open question how resting brains configure their functional organization to balance the demands on network segregation and integration to best serve cognition. Here we use an eigenmode-based approach to identify hierarchical modules in functional brain networks and quantify the functional balance between network segregation and integration. In a large sample of healthy young adults (n = 991), we combine the whole-brain resting state functional magnetic resonance imaging (fMRI) data with a mean-filed model on the structural network derived from diffusion tensor imaging and demonstrate that resting brain networks are on average close to a balanced state. This state allows for a balanced time dwelling at segregated and integrated configurations and highly flexible switching between them. Furthermore, we employ structural equation modeling to estimate general and domain-specific cognitive phenotypes from nine tasks and demonstrate that network segregation, integration, and their balance in resting brains predict individual differences in diverse cognitive phenotypes. More specifically, stronger integration is associated with better general cognitive ability, stronger segregation fosters crystallized intelligence and processing speed, and an individual's tendency toward balance supports better memory. Our findings provide a comprehensive and deep understanding of the brain's functioning principles in supporting diverse functional demands and cognitive abilities and advance modern network neuroscience theories of human cognition.

Indexed as

AdultBrainBrain MappingCognitionDiffusion Tensor ImagingFemaleHumansMagnetic Resonance ImagingMaleNerve NetRestYoung Adultfunctional brain networkhierarchical moduleshuman cognitionsegregation–integration balancestructural equation modeling

Identifiers

PMID34074762
PMCPMC8201916

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.