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脑网络模块化可预测老年人与运动相关的执行功能改善情况。

Brain Network Modularity Predicts Exercise-Related Executive Function Gains in Older Adults.

作者信息

Baniqued Pauline L, Gallen Courtney L, Voss Michelle W, Burzynska Agnieszka Z, Wong Chelsea N, Cooke Gillian E, Duffy Kristin, Fanning Jason, Ehlers Diane K, Salerno Elizabeth A, Aguiñaga Susan, McAuley Edward, Kramer Arthur F, D'Esposito Mark

机构信息

Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, United States.

Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, United States.

出版信息

Front Aging Neurosci. 2018 Jan 4;9:426. doi: 10.3389/fnagi.2017.00426. eCollection 2017.

Abstract

Recent work suggests that the brain can be conceptualized as a network comprised of groups of sub-networks or modules. The extent of segregation between modules can be quantified with a modularity metric, where networks with high modularity have dense connections within modules and sparser connections between modules. Previous work has shown that higher modularity predicts greater improvements after cognitive training in patients with traumatic brain injury and in healthy older and young adults. It is not known, however, whether modularity can also predict cognitive gains after a physical exercise intervention. Here, we quantified modularity in older adults ( = 128, mean age = 64.74) who underwent one of the following interventions for 6 months (NCT01472744 on ClinicalTrials.gov): (1) aerobic exercise in the form of brisk walking (Walk), (2) aerobic exercise in the form of brisk walking plus nutritional supplement (Walk+), (3) stretching, strengthening and stability (SSS), or (4) dance instruction. After the intervention, the Walk, Walk+ and SSS groups showed gains in cardiorespiratory fitness (CRF), with larger effects in both walking groups compared to the SSS and Dance groups. The Walk, Walk+ and SSS groups also improved in executive function (EF) as measured by reasoning, working memory, and task-switching tests. In the Walk, Walk+, and SSS groups that improved in EF, higher baseline modularity was positively related to EF gains, even after controlling for age, in-scanner motion and baseline EF. No relationship between modularity and EF gains was observed in the Dance group, which did not show training-related gains in CRF or EF control. These results are consistent with previous studies demonstrating that individuals with a more modular brain network organization are more responsive to cognitive training. These findings suggest that the predictive power of modularity may be generalizable across interventions aimed to enhance aspects of cognition and that, especially in low-performing individuals, global network properties can capture individual differences in neuroplasticity.

摘要

近期研究表明,大脑可被概念化为一个由子网络或模块组构成的网络。模块之间的分离程度可用模块化度量来量化,模块化程度高的网络在模块内部连接紧密,而模块之间的连接较为稀疏。先前的研究表明,更高的模块化程度预示着创伤性脑损伤患者以及健康的老年人和年轻人在认知训练后会有更大的改善。然而,尚不清楚模块化程度是否也能预测体育锻炼干预后的认知提升。在此,我们对128名老年人(平均年龄 = 64.74岁)的模块化程度进行了量化,这些老年人参加了以下干预措施之一,为期6个月(ClinicalTrials.gov上的NCT01472744):(1)快走形式的有氧运动(步行组),(2)快走形式的有氧运动加营养补充剂(步行 + 组),(3)拉伸、强化和稳定性训练(SSS组),或(4)舞蹈指导。干预后,步行组、步行 + 组和SSS组的心肺适能(CRF)有所提高,与SSS组和舞蹈组相比,两个步行组的效果更明显。步行组、步行 + 组和SSS组在执行功能(EF)方面也有改善,通过推理、工作记忆和任务转换测试进行测量。在EF得到改善的步行组、步行 + 组和SSS组中,即使在控制了年龄、扫描器内运动和基线EF后,更高的基线模块化程度与EF的提升呈正相关。在舞蹈组中未观察到模块化程度与EF提升之间的关系,该组在CRF或EF控制方面未显示出与训练相关的改善。这些结果与先前的研究一致,表明大脑网络组织模块化程度更高的个体对认知训练的反应更敏感。这些发现表明,模块化程度的预测能力可能适用于旨在增强认知方面的各种干预措施,并且,特别是在表现较差的个体中,全局网络特性可以捕捉神经可塑性的个体差异。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a63f/5758542/0147ab801794/fnagi-09-00426-g0001.jpg

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