Evidence map›Paper›PMID 37715923›Full record

ArticleNeuroscience bulletin2024

Reshaping the Cortical Connectivity Gradient by Long-Term Cognitive Training During Development.

Tianyong Xu, Yunying Wu, Yi Zhang, Xi-Nian Zuo, Feiyan Chen, Changsong Zhou

Abstract read
In one paragraph

Article in Neuroscience bulletin, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
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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

6 authors.

Tianyong XuBio-X Laboratory, School of Physics, Zhejiang University, Hangzhou, 310027, China.
Yunying WuQiushi Academy for Advanced Studies, Zhejiang University, Hangzhou, 310027, China.
Yi ZhangBio-X Laboratory, School of Physics, Zhejiang University, Hangzhou, 310027, China.
Xi-Nian ZuoState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China.
Feiyan ChenBio-X Laboratory, School of Physics, Zhejiang University, Hangzhou, 310027, China. chenfy@zju.edu.cn.
Changsong ZhouBio-X Laboratory, School of Physics, Zhejiang University, Hangzhou, 310027, China. cszhou@hkbu.edu.hk.ORCID http://orcid.org/0000-0002-4130-0216

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The organization of the brain follows a topological hierarchy that changes dynamically during development. However, it remains unknown whether and how cognitive training administered over multiple years during development can modify this hierarchical topology. By measuring the brain and behavior of school children who had carried out abacus-based mental calculation (AMC) training for five years (starting from 7 years to 12 years old) in pre-training and post-training, we revealed the reshaping effect of long-term AMC intervention during development on the brain hierarchical topology. We observed the development-induced emergence of the default network, AMC training-promoted shifting, and regional changes in cortical gradients. Moreover, the training-induced gradient changes were located in visual and somatomotor areas in association with the visuospatial/motor-imagery strategy. We found that gradient-based features can predict the math ability within groups. Our findings provide novel insights into the dynamic nature of network recruitment impacted by long-term cognitive training during development.

Indexed as

Cognitive TrainingMotor CortexBrainBrain MappingChildHumansMagnetic Resonance ImagingAbacus-based mental calculationCognitive trainingConnectivity gradientDevelopmentNeural plasticity

Identifiers

PMID37715923
PMCPMC10774512

What OpenQuestion holds

Textmetadata
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.