离散的里奇曲线捕捉了人类大脑功能连接网络中与年龄相关的变化
Yasharth Yadav1,2, Pavithra Elumalai1, Nitin Williams3,4
1The Institute of Mathematical Sciences (IMSc), Chennai, India.
Frontiers in aging neuroscience
|June 9, 2023
概括
离散的里奇曲率测量揭示了与年龄相关的大脑功能连接的变化. 这些以几何学为灵感的方法突出显示了参与运动和情绪处理的大脑区域,为认知衰老提供了新的见解.
科学领域:
- 神经科学是一个神经科学.
- 网络科学 网络科学
- 计算解剖学的计算解剖学
背景情况:
- 离散的里奇曲线用于检测神经精神疾病中大脑连接的破坏.
- 它的应用来表征与年龄相关的功能连接性变化仍然未被探索.
研究的目的:
- 调查福曼-里奇和奥利维埃-里奇曲线在表征与年龄相关的功能连接差异方面的有用性.
- 探索这些曲率差异与认知功能和行为结果的关联.
主要方法:
- 应用福曼-里奇和奥利维尔-里奇曲线到功能连接网络.
- 从MPI-LEMON数据集中对健康的年轻人和老年人的网络进行比较 (N=225).
- 利用元分析解码和与行为得分相关联的曲率.
主要成果:
- 两种曲率测量都检测到全脑和区域年龄相关的功能连接差异.
- 与年龄相关的曲率差异的区域与运动,情感和体感处理有关.
- 曲率值与情感处理行为相关,并与受益于非侵入性运动刺激的区域重叠.
结论:
- 福曼-里奇和奥利维尔-里奇曲线有效地识别功能和临床相关的大脑区域.
- 离散的里奇曲线对与年龄相关的功能连接组织变化敏感.
- 这些发现支持使用离散的里奇曲率来理解老化和疾病中的大脑网络变化.
关键词:
福曼 - 里奇曲线这就是MPI-LEMON.奥利维埃 - 里奇曲线功能连接网络的功能连接网络.健康的衰老健康的衰老发动机的性能 发动机的性能非侵入性大脑刺激的非侵入性大脑刺激静止状态的fMRI进行.更多相关视频
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