The functional implications and modifiability of resting-state brain network complexity in older adults

老年人静息态脑网络复杂性的功能意义和可塑性

阅读:1

Abstract

The dynamics of the resting-state activity in brain functional networks are complex, containing meaningful patterns over multiple temporal scales. Such physiologic complexity is often diminished in older adults. Here we aim to examine if the resting-state complexity within functional brain networks is sensitive to functional status in older adults and if repeated exposure to transcranial direct current stimulation (tDCS) would modulate such complexity. Twelve older adults with slow gait and mild-to-moderate executive dysfunction and 12 age- and sex-matched controls completed a baseline resting-state fMRI (rs-fMRI). Ten participants in the functionally-limited group then completed ten 20-minute sessions of real (n = 6) or sham (n = 4) tDCS targeting the left prefrontal cortex over a two-week period as well as a follow-up rs-fMRI. The resting-state complexity associated with seven functional networks was quantified by averaging the multiscale entropy (MSE) of the blood oxygen level-dependent (BOLD) time-series for all voxels within each network. Compared to controls, functionally-limited group exhibited lower complexity in the motor, ventral attention, limbic, executive and default mode networks (F > 6.3, p < 0.02). Within this group, those who received tDCS exhibited greater complexity within the ventral, executive and limbic networks (p < 0.04) post intervention as compared to baseline, while no significant changes in sham group was observed. This study provides preliminary evidence that older adults with functional limitations had diminished complexity of resting-state brain network activity and repeated exposure to tDCS may increase that resting-state complexity, warranting future studies to establish such complexity as a marker of brain health in older adults.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。