Brain markers of subtraction and multiplication skills in childhood: task-based functional connectivity and individualized structural similarity.

IF 2.9 2区 医学 Q2 NEUROSCIENCES Cerebral cortex Pub Date : 2024-09-03 DOI:10.1093/cercor/bhae374
Zheng Li, Haifeng Fang, Weiguo Fan, Jiaoyu Wu, Jiaxin Cui, Bao-Ming Li, Chunjie Wang
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Abstract

Arithmetic, a high-order cognitive ability, show marked individual difference over development. Despite recent advancements in neuroimaging techniques have enabled the identification of brain markers for individual differences in high-order cognitive abilities, it remains largely unknown about the brain markers for arithmetic. This study used a data-driven connectome-based prediction model to identify brain markers of arithmetic skills from arithmetic-state functional connectivity and individualized structural similarity in 132 children aged 8 to 15 years. We found that both subtraction-state functional connectivity and individualized SS successfully predicted subtraction and multiplication skills but multiplication-state functional connectivity failed to predict either skill. Among the four successful prediction models, most predictive connections were located in frontal-parietal, default-mode, and secondary visual networks. Further computational lesion analyses revealed the essential structural role of frontal-parietal network in predicting subtraction and the essential functional roles of secondary visual, language, and ventral multimodal networks in predicting multiplication. Finally, a few shared nodes but largely nonoverlapping functional and structural connections were found to predict subtraction and multiplication skills. Altogether, our findings provide new insights into the brain markers of arithmetic skills in children and highlight the importance of studying different connectivity modalities and different arithmetic domains to advance our understanding of children's arithmetic skills.

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儿童时期减法和乘法技能的大脑标记:基于任务的功能连接和个性化结构相似性。
算术作为一种高阶认知能力,在发育过程中表现出明显的个体差异。尽管近年来神经成像技术的进步使人们能够识别高阶认知能力个体差异的大脑标志物,但人们对算术的大脑标志物仍然知之甚少。本研究利用基于数据驱动的连接组预测模型,从132名8至15岁儿童的算术状态功能连接性和个体化结构相似性中识别出算术能力的大脑标记。我们发现,减法状态功能连通性和个体化结构相似性都能成功预测减法和乘法技能,但乘法状态功能连通性却不能预测这两种技能。在四个成功的预测模型中,大多数预测连接位于额叶-顶叶、默认模式和二级视觉网络。进一步的计算损伤分析表明,额叶-顶叶网络在预测减法中起着重要的结构作用,而二级视觉、语言和腹侧多模态网络在预测乘法中起着重要的功能作用。最后,我们还发现了一些共享的节点,但这些节点在功能和结构上基本没有重叠,从而预测了减法和乘法技能。总之,我们的研究结果为儿童算术技能的大脑标记提供了新的见解,并强调了研究不同连接模式和不同算术领域对促进我们了解儿童算术技能的重要性。
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来源期刊
Cerebral cortex
Cerebral cortex 医学-神经科学
CiteScore
6.30
自引率
8.10%
发文量
510
审稿时长
2 months
期刊介绍: Cerebral Cortex publishes papers on the development, organization, plasticity, and function of the cerebral cortex, including the hippocampus. Studies with clear relevance to the cerebral cortex, such as the thalamocortical relationship or cortico-subcortical interactions, are also included. The journal is multidisciplinary and covers the large variety of modern neurobiological and neuropsychological techniques, including anatomy, biochemistry, molecular neurobiology, electrophysiology, behavior, artificial intelligence, and theoretical modeling. In addition to research articles, special features such as brief reviews, book reviews, and commentaries are included.
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My science and career with Joseph E. LeDoux. Individual differences in functional connectivity during suppression of imagined threat. When emotion and time meet from human and rodent perspectives: a central role for the amygdala? Introspective psychophysics for the study of subjective experience. Examining threat responses through a developmental lens.
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