健康衰老中的认知灵活性和大脑网络能量:从SENECA模型的全静态视角
Clément Guichet1, Sophie Achard2, Martial Mermillod1
1Univ. Grenoble Alpes, CNRS LPNC UMR 5105, Grenoble, France.
Imaging neuroscience (Cambridge, Mass.)
|January 15, 2026
概括
中年是大脑网络灵活性的一个关键过渡期. 大脑能量从高层网络转移到低层网络,保持功能并支持老年人的认知灵活性.
科学领域:
- 神经科学是一个神经科学.
- 认知科学 认知科学
- 衰老研究研究 衰老研究
背景情况:
- 维持老年人的认知灵活性是衰老研究中的一个关键挑战.
- 了解与年龄相关的认知变化背后的神经机制至关重要.
研究的目的:
- 研究老年大脑如何保持认知灵活性.
- 探索功能网络能量及其在整个生命周期中的重组的作用.
主要方法:
- 来自基于人口的CamCAN数据库 (N=628,年龄18-88) 的静止状态fMRI数据的分析.
- 应用结构平衡理论来测量功能网络能量作为网络灵活性的代理.
- 检查网络能量再分配沿着感官-跨模态层次结构.
主要成果:
- 中年被认为是大脑网络重组的关键过渡期.
- 功能网络的能量从更高层次的网络 (默认模式网络-前对联网络) 转移到更低层次的网络 (感官运动网络,认知控制网络,听觉,视觉和语言网络).
- 这种重组保护了全球电线经济,并支持在老年成人中体现的语义策略,可能是通过预测处理.
结论:
- 健康的神经认知衰老可以重新定义为一个全静态过程 (通过变化稳定).
- 这些发现为将SENECA模型扩展到新陈代谢和神经病理学提供了参考.
- 整个生命周期中大脑网络的重组是维持衰老过程中认知灵活性的关键机制.
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