老年人久坐的生活方式的神经决定因素:大脑网络分析
Mohsen Bahrami1,2, Jonathan H Burdette1,2, Paul J Laurienti1,2
1Laboratory for Complex Brain Networks, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA.
Brain and behavior
|January 8, 2025
概括
老年人的久坐不动的生活方式与自我调节网络中的大脑活动有关. 机器学习识别了这些电路,以超过92%的准确度预测了坐着时间和日常步骤的变化.
科学领域:
- 老年学是一门学科.
- 神经科学是一个神经科学.
- 公共卫生 公共卫生
背景情况:
- 久坐不动的生活方式 (SL) 在老年人中越来越普遍,导致并发病和失去独立性.
- 公共卫生指导方针现在鼓励减少坐着的时间和增加每天的步骤.
- 之前的一项研究调查了减肥 (WL) 以及针对坐时间和步骤的SitLess干预.
研究的目的:
- 识别与坐时间和日常步骤变化相关的大脑电路.
- 为了确定机器学习是否可以预测这些行为变化.
- 了解老年人久坐行为干预的神经基础.
主要方法:
- 利用了36名参与者的基线fMRI和加速度计数据.
- 应用先进的机器学习工具来分析数据.
- 集中在6个月的强化阶段随机分配给WL + SitLess条件的参与者.
主要成果:
- 机器学习模型准确地预测了坐时间和每天步骤的前后变化 (>92%的准确性).
- 确定的大脑子网络在行为变化中发挥着关键作用.
- 网络涉及默认模式和与自我监管和决策相关的感觉运动区域.
结论:
- 研究结果提供了对老年人久坐不动生活方式的理论基础的见解.
- 结果可以为未来旨在减少久坐行为的干预措施的设计提供信息.
- 强调神经自我调节机制在体育活动干预措施中的重要性.
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