Abstract

The current study investigates the utility of resting-state EEG coherence values in predicting standardized math scores in children. Quantitative EEG and standardized academic achievement analyses were performed on 60 school-aged children. Analyses assessing intrahemispheric coherence at rest were conducted across the sample of participants and several coherence networks were extracted and compared to standardized math achievement values. Specifically, networks that included Brodmann area 40 (a brain region involved in the cognitive processes responsible for mathematics performance) and whose coherence values were significantly correlated with standardized math scores were examined. Results indicate a total of four coherence networks, two in each hemisphere, that have utility in predicting general math skills in children. In addition to BA 40, these coherence networks include BAs in the right temporal lobe, right frontoparietal lobe, left superior temporal lobe, and the left medial prefrontal cortex. These findings address the current dearth of research on the neurological connectivity patterns that are foundational for mathematics abilities in children. Further, these results lay a foundation for the supplementary use of EEG in the assessment and identification practices surrounding math learning disabilities in children and additionally provide a neurocognitive framework upon which intervention research may be targeted.

摘要

目前的研究调查了静息状态脑电图一致性值在预测儿童标准化数学成绩中的效用。对 60 名学龄儿童进行了定量脑电图和标准化学业成绩分析。在参与者样本中进行了评估休息时大脑半球内连贯性的分析，并提取了几个连贯网络并与标准化的数学成绩值进行比较。具体来说，检查了包括 Brodmann 40 区（参与负责数学表现的认知过程的大脑区域）以及其连贯性值与标准化数学分数显着相关的网络。结果表明，共有四个相干网络，每个半球两个，可用于预测儿童的一般数学技能。除了 BA 40，这些连贯网络包括右颞叶、右额顶叶、左上颞叶和左内侧前额叶皮层的 BA。这些发现解决了目前缺乏对儿童数学能力基础的神经连接模式的研究。此外，这些结果为脑电图在儿童数学学习障碍的评估和识别实践中的补充使用奠定了基础，另外还提供了一个神经认知框架，干预研究可以作为目标。这些发现解决了目前缺乏对儿童数学能力基础的神经连接模式的研究。此外，这些结果为脑电图在儿童数学学习障碍的评估和识别实践中的补充使用奠定了基础，另外还提供了一个神经认知框架，干预研究可以作为目标。这些发现解决了目前缺乏对儿童数学能力基础的神经连接模式的研究。此外，这些结果为脑电图在儿童数学学习障碍的评估和识别实践中的补充使用奠定了基础，另外还提供了一个神经认知框架，干预研究可以作为目标。