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Plasticity of left perisylvian white-matter tracts is associated with individual differences in math learning

机译:左周囊白质物质的可塑性与数学学习中的个体差异有关

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Plasticity of white matter tracts is thought to be essential for cognitive development and academic skill acquisition in children. However, a dearth of high-quality diffusion tensor imaging (DTI) data measuring longitudinal changes with learning, as well as methodological difficulties in multi-time point tract identification have limited our ability to investigate plasticity of specific white matter tracts. Here, we examine learning-related changes of white matter tracts innervating inferior parietal, prefrontal and temporal regions following an intense 2-month math tutoring program. DTI data were acquired from 18 third grade children, both before and after tutoring. A novel fiber tracking algorithm based on a White Matter Query Language (WMQL) was used to identify three sections of the superior longitudinal fasciculus (SLF) linking frontal and parietal (SLF-FP), parietal and temporal (SLF-PT) and frontal and temporal (SLF-FT) cortices, from which we created child-specific probabilistic maps. The SLF-FP, SLF-FT, and SLF-PT tracts identified with the WMQL method were highly reliable across the two time points and showed close correspondence to tracts previously described in adults. Notably, individual differences in behavioral gains after 2 months of tutoring were specifically correlated with plasticity in the left SLF-FT tract. Our results extend previous findings of individual differences in white matter integrity, and provide important new insights into white matter plasticity related to math learning in childhood. More generally, our quantitative approach will be useful for future studies examining longitudinal changes in white matter integrity associated with cognitive skill development.
机译:白质束的可塑性被认为对于儿童的认知发展和学习技能的获取至关重要。但是,缺乏测量随学习的纵向变化的高质量扩散张量成像(DTI)数据,以及在多时间点道识别中方法上的困难限制了我们研究特定白质道可塑性的能力。在这里,我们研究了为期2个月的严格数学辅导计划后,与神经质相关的白质束变化,神经质作用于壁下,额叶和颞下区域。在辅导之前和之后,均从18名三年级孩子那里获得了DTI数据。一种新的基于白色物质查询语言(WMQL)的纤维跟踪算法用于识别上额筋膜(SLF)的三个部分,这些部分连接额叶和顶叶(SLF-FP),顶叶和颞叶(SLF-PT)以及额叶和额叶颞(SLF-FT)皮质,我们从中创建了儿童特定的概率图。用WMQL方法确定的SLF-FP,SLF-FT和SLF-PT道在两个时间点上都是高度可靠的,并且显示出与先前在成人中描述过的道密切相关。值得注意的是,补习2个月后行为获得的个体差异与左SLF-FT道的可塑性特别相关。我们的结果扩展了先前关于白质完整性个体差异的发现,并为与童年数学学习相关的白质可塑性提供了重要的新见解。更广泛地说,我们的定量方法将对未来研究与认知能力发展相关的白质完整性的纵向变化有用。

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