Evidence map›Paper›PMID 40230021›Full record

ArticleHuman brain mapping2025

Dynamic Functional Network Connectivity Pattern of the Amygdalohippocampal Complex in Individuals With Subjective Cognitive Decline.

Chih-Kai Lee, Xiao-Ya Wei, Ze-Yi Wang, Hang Zhou, Chao-Qun Yan, Xin-Yuan Jiang, Guang-Xia Shi, Xu Wang, Cun-Zhi Liu

Abstract read
In one paragraph

Article in Human brain mapping, 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

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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. Review
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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

9 authors.

Chih-Kai LeeInternational Acupuncture and Moxibustion Innovation Institute, School of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese Medicine, Beijing, China.ORCID 0009-0007-6991-5048
Xiao-Ya WeiInternational Acupuncture and Moxibustion Innovation Institute, School of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese Medicine, Beijing, China.
Ze-Yi WangInternational Acupuncture and Moxibustion Innovation Institute, School of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese Medicine, Beijing, China.
Hang ZhouInternational Acupuncture and Moxibustion Innovation Institute, School of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese Medicine, Beijing, China.
Chao-Qun YanDongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China.
Xin-Yuan JiangSchool of Life Sciences, Beijing University of Chinese Medicine, Beijing, China.
Guang-Xia ShiInternational Acupuncture and Moxibustion Innovation Institute, School of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese Medicine, Beijing, China.
Xu WangSchool of Life Sciences, Beijing University of Chinese Medicine, Beijing, China.
Cun-Zhi LiuInternational Acupuncture and Moxibustion Innovation Institute, School of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese Medicine, Beijing, China.ORCID 0000-0001-8031-5667

Funding

National Natural Science Foundation of China 81674055
6 · The paper itself

Abstract

Subjective cognitive decline (SCD) is a potential early marker of cognitive decline and dementia. The amygdalohippocampal structure and function are closely related to cognitive decline, but few studies have investigated large-scale amygdalohippocampal brain functional network connectivity in individuals with SCD. Here, we aim to explore how the dynamic functional network connectivity (dFNC) between the amygdalohippocampal complex and other brain networks contributes to the understanding of early cognitive decline. Independent component analysis (ICA) and dFNC analysis were applied to functional magnetic resonance imaging (fMRI) data from 66 individuals with SCD to extract the amygdalohippocampal complex and identify distinct connectivity states. Cognitive performance was assessed through a composite Z score derived from a battery of neuropsychological tests. Correlation analyses were performed to examine the associations between the dFNC patterns and cognitive performance. Three distinct dFNC states were identified, each characterized by varying levels of within- and inter-network connectivity, with occurrences of 65%, 18%, and 17% respectively. Cognitive function, measured using a composite Z score, was positively correlated with amygdalohippocampal-sensorimotor network (SM) and amygdalohippocampal-visual network (VI) dFNC in State 2. Significant correlations were observed between the amygdalohippocampal complex and the left precentral gyrus (r = 0.517, FDR-corrected p = 0.005), postcentral gyrus (r = 0.487, FDR-corrected p = 0.034), and multiple visual network regions, including the lingual gyrus and lateral occipital cortex (all Ps < 0.05, FDR-corrected). These associations remained significant after adjusting for sex and age. These findings extend the current understanding of amygdalohippocampal dysfunction in cognitive decline and demonstrate that cognitive function is associated with distinct large-scale amygdalohippocampal network dynamics.

Indexed as

AmygdalaCognitive DysfunctionConnectomeHippocampusNerve NetAdultAgedFemaleHumansMagnetic Resonance ImagingMaleMiddle Agedamygdalohippocampal complexdynamic functional network connectivityfMRIindependent component analysissubjective cognitive decline

Identifiers

PMID40230021
PMCPMC11997012

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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.