分布式fMRI模式与低频心肺呼吸动态相结合,提供了衰老标志物
Shiyu Wang1, Richard Song2,3, Laurent M Lochard4
1Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, 37240, USA.
概括
衰老会影响大脑与身体的连接. 功能磁共振成像 (fMRI) 模式与生理信号相结合可靠地预测年龄,突出自主调节.
科学领域:
- 神经科学是一个神经科学.
- 衰老研究研究 衰老研究
- 身体生理学 身体生理学
背景情况:
- 衰老会改变大脑与身体的连接,可以通过功能磁共振成像 (fMRI) 和自主过程进行测量.
- 之前的研究指出,与年龄相关的变化,在特定的大脑区域和生理活动之间的关联.
- 大脑活动和生理信号之间的相互作用越来越被认为是重要的,超越了"噪音"的解释.
研究的目的:
- 研究与低频生理过程相关的全脑空间fMRI模式的与年龄相关的变化.
- 为了确定这些fMRI-生理学合模式是否可以预测成年人寿命中的时间年龄.
- 根据fMRI-生理学合,确定对预测年龄最有影响力的大脑区域.
主要方法:
- 分析功能磁共振成像 (fMRI) 数据从人类参与者整个成年人寿.
- 检查fMRI-生理学合的全脑空间模式,重点关注低频心率和呼吸量波动.
- 从fMRI-生理学合模式来统计预测时间年龄,控制生理信号特征和大脑解剖学.
主要成果:
- 从低频fMRI-生理学合模式来看,时间年龄在统计上是可预测的.
- 参与中央自主调节的大脑区域 (例如,胰岛,中带皮层) 是年龄的关键预测因素.
- 剩余血液氧气水平依赖 (BOLD) 信号变化,即使考虑到生理效应,仍然是一个可靠的年龄指标.
结论:
- fMRI-生理学合模式揭示了大脑与身体融合中的可概括的与年龄相关的变化.
- 这种合是衰老过程的潜在生物标志物,反映了自主功能和大脑血管健康的变化.
- 这些发现强调了大脑与身体相互作用在理解衰老和潜在的疾病相关干扰方面的重要性.
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