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Brain Network Modularity Predicts Improvements in Cognitive and Scholastic Performance in Children Involved in a Physical Activity Intervention
Frontiers in Human Neuroscience ( IF 2.4 ) Pub Date : 2020-09-03 , DOI: 10.3389/fnhum.2020.00346
Laura Chaddock-Heyman , Timothy B. Weng , Caitlin Kienzler , Robert Weisshappel , Eric S. Drollette , Lauren B. Raine , Daniel R. Westfall , Shih-Chun Kao , Pauline Baniqued , Darla M. Castelli , Charles H. Hillman , Arthur F. Kramer

Introduction: Brain network modularity is a principle that quantifies the degree to which functional brain networks are divided into subnetworks. Higher modularity reflects a greater number of within-module connections and fewer connections between modules, and a highly modular brain is often interpreted as a brain that contains highly specialized brain networks with less integration between networks. Recent work in younger and older adults has demonstrated that individual differences in brain network modularity at baseline can predict improvements in performance after cognitive and physical interventions. The use of brain network modularity as a predictor of training outcomes has not yet been examined in children. Method: In the present study, we examined the relationship between baseline brain network modularity and changes (post-intervention performance minus pre-intervention performance) in cognitive and academic performance in 8- to 9-year-old children who participated in an after-school physical activity intervention for 9 months (N = 78) as well as in children in a wait-list control group (N = 72). Results: In children involved in the after-school physical activity intervention, higher modularity of brain networks at baseline predicted greater improvements in cognitive performance for tasks of executive function, cognitive efficiency, and mathematics achievement. There were no associations between baseline brain network modularity and performance changes in the wait-list control group. Discussion: Our study has implications for biomarkers of cognitive plasticity in children. Understanding predictors of cognitive performance and academic progress during child development may facilitate the effectiveness of interventions aimed to improve cognitive and brain health.

中文翻译:

脑网络模块化预测参与体育活动干预的儿童认知和学习成绩的改善

简介:脑网络模块化是一种量化功能性脑网络划分子网络程度的原则。更高的模块化反映了更多的模块内连接和更少的模块之间的连接,高度模块化的大脑通常被解释为包含高度专业化的大脑网络,网络之间的集成较少的大脑。最近对年轻人和老年人的研究表明,基线时大脑网络模块性的个体差异可以预测认知和身体干预后的表现改善。尚未在儿童中检查使用大脑网络模块化作为训练结果的预测指标。方法:在本研究中,我们检查了参加课后体育活动干预 9 个月的 8 至 9 岁儿童的基线脑网络模块性与认知和学业成绩变化(干预后表现减去干预前表现)之间的关系(N = 78) 以及等待名单对照组中的儿童 (N = 72)。结果:在参与课后体育活动干预的儿童中,基线时大脑网络的模块化程度越高,其在执行功能、认知效率和数学成绩等任务的认知表现方面的改善程度越大。在候补名单对照组中,基线脑网络模块性与表现变化之间没有关联。讨论:我们的研究对儿童认知可塑性的生物标志物有影响。
更新日期:2020-09-03
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