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去分化的电生理特征在健康状况较好和较差的老年人之间存在差异。

Electrophysiological signatures of dedifferentiation differ between fit and less fit older adults.

作者信息

Goelz Christian, Mora Karin, Stroehlein Julia Kristin, Haase Franziska Katharina, Dellnitz Michael, Reinsberger Claus, Vieluf Solveig

机构信息

Institute of Sports Medicine, Paderborn University, Warburger Str. 100, 33098 Paderborn, Germany.

Department of Mathematics, Paderborn University, Paderborn, Germany.

出版信息

Cogn Neurodyn. 2021 Oct;15(5):847-859. doi: 10.1007/s11571-020-09656-9. Epub 2021 Feb 6.

Abstract

UNLABELLED

Cardiorespiratory fitness was found to influence age-related changes of resting state brain network organization. However, the influence on dedifferentiated involvement of wider and more unspecialized brain regions during task completion is barely understood. We analyzed EEG data recorded during rest and different tasks (sensory, motor, cognitive) with dynamic mode decomposition, which accounts for topological characteristics as well as temporal dynamics of brain networks. As a main feature the dominant spatio-temporal EEG pattern was extracted in multiple frequency bands per participant. To deduce a pattern's stability, we calculated its proportion of total variance among all activation patterns over time for each task. By comparing fit (N = 15) and less fit older adults (N = 16) characterized by their performance on a 6-min walking test, we found signs of a lower task specificity of the obtained network features for the less fit compared to the fit group. This was indicated by fewer significant differences between tasks in the theta and high beta frequency band in the less fit group. Repeated measures ANOVA revealed that a significantly lower proportion of total variance can be explained by the main pattern in high beta frequency range for the less fit compared to the fit group [F(1,29) = 12.572,  = .001, partial η = .300]. Our results indicate that the dedifferentiation in task-related brain activation is lower in fit compared to less fit older adults. Thus, our study supports the idea that cardiorespiratory fitness influences task-related brain network organization in different task domains.

SUPPLEMENTARY INFORMATION

The online version of this article (10.1007/s11571-020-09656-9) contains supplementary material, which is available to authorized users.

摘要

未标注

研究发现心肺适能会影响静息态脑网络组织的年龄相关变化。然而,对于任务完成过程中更广泛、更不专门化的脑区去分化参与的影响却知之甚少。我们使用动态模式分解分析了静息和不同任务(感觉、运动、认知)期间记录的脑电图数据,该方法考虑了脑网络的拓扑特征以及时间动态。作为主要特征,为每个参与者在多个频段中提取了占主导地位的时空脑电图模式。为了推断模式的稳定性,我们计算了每个任务随时间所有激活模式中其总方差的比例。通过比较以6分钟步行测试表现为特征的健康老年人(N = 15)和身体状况较差的老年人(N = 16),我们发现与健康组相比,身体状况较差的组所获得的网络特征的任务特异性较低。这表现为身体状况较差的组在θ波和高β频段任务之间的显著差异较少。重复测量方差分析显示,与健康组相比,身体状况较差的组在高β频率范围内主要模式所能解释的总方差比例显著更低[F(1,29) = 12.572,P = .001,偏η = .300]。我们的结果表明,与身体状况较差的老年人相比,健康老年人在任务相关脑激活中的去分化程度更低。因此,我们的研究支持心肺适能会影响不同任务领域中任务相关脑网络组织这一观点。

补充信息

本文的在线版本(10.1007/s11571-020-09656-9)包含补充材料,授权用户可获取。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f645/8448815/58b4e762a1ad/11571_2020_9656_Fig1_HTML.jpg

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