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Temporo-frontal activation during phonological processing predicts gains in arithmetic facts in young children.
Developmental Cognitive Neuroscience ( IF 4.6 ) Pub Date : 2019-11-12 , DOI: 10.1016/j.dcn.2019.100735
Macarena Suárez-Pellicioni 1 , Lynn Fuchs 2 , James R Booth 1
Affiliation  

Behavioral studies have shown discrepant results regarding the role of phonology in predicting math gains. The objective of this study was to use fMRI to study the role of activation during a rhyming judgment task in predicting behavioral gains on math fluency, multiplication, and subtraction skill. We focused within the left middle/superior temporal gyrus and left inferior frontal gyrus, brain areas associated with the storage of phonological representations and with their access, respectively. We ran multiple regression analyses to determine whether activation predicted gains in the three math measures, separately for younger (i.e. 10 years old) and older (i.e 12 years old) children. Results showed that activation in both temporal and frontal cortex only predicted gains in fluency and multiplication skill, and only for younger children. This study suggests that both temporal and frontal cortex activation during phonological processing are important in predicting gains in math tasks that involve the retrieval of facts that are stored as phonological codes in memory. Moreover, these results were specific to younger children, suggesting that phonology is most important in the early stages of math development. When the math task involved subtractions, which relies on quantity representations, phonological processes were not important in driving gains.



中文翻译:

语音处理过程中颞额叶的激活可以预测幼儿算术事实的增长。

行为研究表明,关于音韵学在预测数学成绩方面的作用,结果存在差异。本研究的目的是利用功能磁共振成像来研究押韵判断任务中激活在预测数学流利度、乘法和减法技能行为增益方面的作用。我们重点关注左中/颞上回和左额下回,这两个大脑区域分别与语音表征的存储及其访问相关。我们进行了多重回归分析,以确定激活是否可以预测三个数学指标的收益,分别针对年龄较小(即 10 岁)和年龄较大(即 12 岁)的儿童。结果表明,颞叶和额叶皮层的激活只能预测流利度和乘法技能的提高,而且仅限于年幼的孩子。这项研究表明,语音处理过程中颞叶皮层和额叶皮层的激活对于预测数学任务的收益非常重要,这些数学任务涉及检索作为语音代码存储在内存中的事实。此外,这些结果是针对年幼的孩子的,这表明语音学在数学发展的早期阶段最为重要。当数学任务涉及减法(依赖于数量表示)时,语音过程在推动收益方面并不重要。

更新日期:2019-11-12
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