Spatiotemporal profiling of functional network overlapping modules in Alzheimer's disease.

Yue Gu, Ying Lin, Liangfang Li, Junji Ma, Sihan Wei, Zhengjia Dai, Alzheimer’s Disease Neuroimaging Initiative

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Article in Network neuroscience (Cambridge, Mass.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

7 authors.

Yue GuDepartment of Psychology, Sun Yat-sen University, Guangzhou, China.

Ying LinDepartment of Psychology, Sun Yat-sen University, Guangzhou, China.

Liangfang LiDepartment of Psychology, Sun Yat-sen University, Guangzhou, China.

Junji MaDepartment of Psychology, Sun Yat-sen University, Guangzhou, China.

Sihan WeiDepartment of Psychology, Sun Yat-sen University, Guangzhou, China.

Zhengjia DaiDepartment of Psychology, Sun Yat-sen University, Guangzhou, China.

Alzheimer’s Disease Neuroimaging Initiative

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Alzheimer's disease (AD) is characterized by progressive neural network degradation. In brain functional networks, overlapping module structures provide more accurate representations of brain function than nonoverlapping structures. Since the involvement of overlapping nodes in multiple modules can vary over time, investigating dynamic functional changes in the brain may provide deeper insights into the structural characteristics of these overlapping modules. However, the spatiotemporal dynamics of overlapping modular brain organization remain unclear. We employed resting-state fMRI to explore the overlapping modular organization and dynamic multilayer modules in 64 AD (Age

Indexed as

Alzheimer’s diseaseMultilayer dynamic networksOverlapping modular organizationOverlapping nodeTemporal variability

Identifiers

PMID41782936

DOI10.1162/NETN.a.516

PMCPMC12956295

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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.