Evidence map›Paper›PMID 39627691›Full record

ArticleBMC neuroscience2024

Older is order: entropy reduction in cortical spontaneous activity marks healthy aging.

Da Chang, Xiu Wang, Yaojing Chen, Zhuo Rachel Han, Yin Wang, Bing Liu, Zhanjun Zhang, Xi-Nian Zuo

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PubMed Full text at PMC Publisher
In one paragraph

Article in BMC neuroscience, 2024. 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

8 authors.

Da ChangState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No 19 Xinjiekouwai Street, Haidian District, Beijing, 100875, China.
Xiu WangDepartment of Neurology, Beijing Chuiyangliu Hospital Affiliated to Tsinghua University, No 2 Chuiyangliunan Street, Chaoyang District, Beijing, 100022, China.
Yaojing ChenBABRI Centre, Beijing Normal University, No 19 Xinjiekouwai Street, Haidian District, Beijing, 100875, China.
Zhuo Rachel HanFaculty of Psychology, Beijing Normal University, No 19 Xinjiekouwai Street, Haidian District, Beijing, 100875, China.
Yin WangState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No 19 Xinjiekouwai Street, Haidian District, Beijing, 100875, China.
Bing LiuState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No 19 Xinjiekouwai Street, Haidian District, Beijing, 100875, China.
Zhanjun ZhangState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No 19 Xinjiekouwai Street, Haidian District, Beijing, 100875, China.
Xi-Nian ZuoState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No 19 Xinjiekouwai Street, Haidian District, Beijing, 100875, China. xinian.zuo@bnu.edu.cn.

Funding

STI 2030 - the major projects of the Brain Science and Brain-Inspired Intelligence Technology 2021ZD0200500
6 · The paper itself

Abstract

backgroundEntropy trajectories remain unclear for the aging process of human brain system due to the lacking of longitudinal neuroimaging resource.

resultsWe used open data from an accelerated longitudinal cohort (PREVENT-AD) that included 24 healthy aging participants followed by 4 years with 5 visits per participant to establish cortical entropy aging curves and distinguish with the effects of age and cohort. This reveals that global cortical entropy decreased with aging, while a significant cohort effect was detectable that people who were born earlier showed higher cortical entropy. Such entropy reductions were also evident for large-scale cortical networks, although with different rates of reduction for different networks. Specifically, the primary and intermediate networks reduce their entropy faster than the higher-order association networks.

conclusionsOur study confirmed that cortical entropy decreases continually in the aging process, both globally and regionally, and we conclude two specific characteristics of the entropy of the human cortex with aging: the shift of the complexity hierarchy and the diversity of complexity strengthen.

Indexed as

Cerebral CortexEntropyHealthy AgingAgedAged, 80 and overAgingElectroencephalographyFemaleHumansLongitudinal StudiesMagnetic Resonance ImagingMaleMiddle AgedNerve NetAgingBrain networkCortical hierarchyEntropyFMRI

Identifiers

PMID39627691
PMCPMC11616130

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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.