儿童算术能力的结构和转录特征

IF 3.6 1区 心理学 Q1 EDUCATION & EDUCATIONAL RESEARCH npj Science of Learning Pub Date : 2024-09-30 DOI:10.1038/s41539-024-00270-6
Dai Zhang, Yanghui Xie, Longsheng Wang, Ke Zhou
{"title":"儿童算术能力的结构和转录特征","authors":"Dai Zhang, Yanghui Xie, Longsheng Wang, Ke Zhou","doi":"10.1038/s41539-024-00270-6","DOIUrl":null,"url":null,"abstract":"<p><p>Arithmetic ability is critical for daily life, academic achievement, career development, and future economic success. Individual differences in arithmetic skills among children and adolescents are related to variations in brain structures. Most existing studies have used hypothesis-driven region of interest analysis. To identify distributed brain regions related to arithmetic ability, we used data-driven cross-validated predictive models to analyze cross-sectional behavioral and structural MRI data in children and adolescents. The gray matter volume (GMV) of widespread brain regions reliably predicted arithmetic abilities measured by the Comprehensive Mathematical Abilities Test. Furthermore, we applied neuroimaging-transcriptome association analysis to explore transcriptional signatures associated with structural patterns of arithmetic ability. Structural patterns of arithmetic ability primarily correlated with transcriptional profiles enriched for genes involved in transmembrane transport and synaptic signaling. Our findings enhance our understanding of the neural and genetic mechanisms underlying children's arithmetic ability and offer a practical predictor for arithmetic skills during development.</p>","PeriodicalId":48503,"journal":{"name":"npj Science of Learning","volume":"9 1","pages":"58"},"PeriodicalIF":3.6000,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11442576/pdf/","citationCount":"0","resultStr":"{\"title\":\"Structural and transcriptional signatures of arithmetic abilities in children.\",\"authors\":\"Dai Zhang, Yanghui Xie, Longsheng Wang, Ke Zhou\",\"doi\":\"10.1038/s41539-024-00270-6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Arithmetic ability is critical for daily life, academic achievement, career development, and future economic success. Individual differences in arithmetic skills among children and adolescents are related to variations in brain structures. Most existing studies have used hypothesis-driven region of interest analysis. To identify distributed brain regions related to arithmetic ability, we used data-driven cross-validated predictive models to analyze cross-sectional behavioral and structural MRI data in children and adolescents. The gray matter volume (GMV) of widespread brain regions reliably predicted arithmetic abilities measured by the Comprehensive Mathematical Abilities Test. Furthermore, we applied neuroimaging-transcriptome association analysis to explore transcriptional signatures associated with structural patterns of arithmetic ability. Structural patterns of arithmetic ability primarily correlated with transcriptional profiles enriched for genes involved in transmembrane transport and synaptic signaling. Our findings enhance our understanding of the neural and genetic mechanisms underlying children's arithmetic ability and offer a practical predictor for arithmetic skills during development.</p>\",\"PeriodicalId\":48503,\"journal\":{\"name\":\"npj Science of Learning\",\"volume\":\"9 1\",\"pages\":\"58\"},\"PeriodicalIF\":3.6000,\"publicationDate\":\"2024-09-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11442576/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"npj Science of Learning\",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"https://doi.org/10.1038/s41539-024-00270-6\",\"RegionNum\":1,\"RegionCategory\":\"心理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"EDUCATION & EDUCATIONAL RESEARCH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"npj Science of Learning","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1038/s41539-024-00270-6","RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"EDUCATION & EDUCATIONAL RESEARCH","Score":null,"Total":0}
引用次数: 0

摘要

算术能力对日常生活、学业成绩、职业发展和未来的经济成功至关重要。儿童和青少年算术能力的个体差异与大脑结构的变化有关。现有研究大多采用假设驱动的兴趣区分析。为了确定与算术能力相关的分布式大脑区域,我们使用数据驱动的交叉验证预测模型来分析儿童和青少年的横断面行为和结构磁共振成像数据。广泛脑区的灰质体积(GMV)可以可靠地预测综合数学能力测试(Comprehensive Mathematical Abilities Test)所测得的算术能力。此外,我们还应用神经成像-转录组关联分析来探索与算术能力结构模式相关的转录特征。算术能力的结构模式主要与参与跨膜转运和突触信号转导的基因的转录特征相关。我们的研究结果加深了我们对儿童算术能力背后的神经和遗传机制的理解,并为算术能力的发展提供了一个实用的预测指标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Structural and transcriptional signatures of arithmetic abilities in children.

Arithmetic ability is critical for daily life, academic achievement, career development, and future economic success. Individual differences in arithmetic skills among children and adolescents are related to variations in brain structures. Most existing studies have used hypothesis-driven region of interest analysis. To identify distributed brain regions related to arithmetic ability, we used data-driven cross-validated predictive models to analyze cross-sectional behavioral and structural MRI data in children and adolescents. The gray matter volume (GMV) of widespread brain regions reliably predicted arithmetic abilities measured by the Comprehensive Mathematical Abilities Test. Furthermore, we applied neuroimaging-transcriptome association analysis to explore transcriptional signatures associated with structural patterns of arithmetic ability. Structural patterns of arithmetic ability primarily correlated with transcriptional profiles enriched for genes involved in transmembrane transport and synaptic signaling. Our findings enhance our understanding of the neural and genetic mechanisms underlying children's arithmetic ability and offer a practical predictor for arithmetic skills during development.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
5.40
自引率
7.10%
发文量
29
期刊最新文献
Feature versus object in interpreting working memory capacity. Mathematics interest, self-efficacy, and anxiety predict STEM career choice in emerging adulthood. Enhancing mathematical learning outcomes through a low-cost single-channel BCI system. Targeted memory reactivation with sleep disruption does not weaken week-old memories. A transient memory lapse in humans 1-3 h after training.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1