皮层和皮层下大脑网络预测普遍的心率
Amy Isabella Sentis1,2, Javier Rasero2,3,4, Peter J Gianaros2,5
1Medical Scientist Training Program, University of Pittsburgh and Carnegie Mellon University, Pittsburgh, PA, USA.
bioRxiv : the preprint server for biology
|January 23, 2024
概括
较高的大脑区域影响静止心率,这是心血管疾病的危险因素. 使用fMRI数据的机器学习模型识别了大脑网络,预测了健康成年人的心率变化.
科学领域:
- 神经科学是一个神经科学.
- 心血管科学 心血管科学
- 计算生物学 计算生物学
背景情况:
- 休息心率是心血管疾病 (CVD) 的已知风险因素.
- 通过脑干建立了心率的自主控制,但更高的大脑区域的参与程度不太清楚.
- 了解脑心相互作用对于评估心血管疾病风险至关重要.
研究的目的:
- 为了确定预测健康成年人静止心率变化的大脑网络.
- 为了研究皮质和皮质下大脑区域在心率调节中的作用.
- 探索大脑对心血管疾病风险的贡献.
主要方法:
- 在功能磁共振成像 (fMRI) 数据上利用机器学习来预测心脏周期 (心跳间隔).
- 使用基于任务和静止状态fMRI的复杂,高维数据集.
- 整合了外围生理记录和个体内重复测量.
主要成果:
- 机器学习模型成功地从全脑fMRI信号中预测了瞬间的心脏周期.
- 与跨个体相比,预测准确性在个体内更高.
- 鉴定出皮层和皮下区域的网络,通常与心理压力有关,作为心脏周期变化的关键预测因素.
结论:
- 大脑网络,特别是那些涉及心理压力的网络,可以显著预测心率变化.
- 这项研究提供了大脑与心脏相互作用影响心血管健康的证据.
- 这些发现代表了向开发基于脑的CVD风险生物标志物迈出的一步.
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