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首页> 外文会议>Annual International Conference of the IEEE Engineering in Medicine and Biology Society >Estimating directed brain-brain and brain-heart connectivity through globally conditioned Granger causality approaches
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Estimating directed brain-brain and brain-heart connectivity through globally conditioned Granger causality approaches

机译：通过全球调节的格兰杰因果关系方法估算指导的脑大脑和脑心连接

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While a large body of research has focused on the study of within-brain physiological networks (i.e. brain connectivity) as well as their disease-related aberration, few investigators have focused on estimating the directionality of these brain-brain interaction which, given the complexity of brain networks, should be properly conditioned in order to avoid the high number of false positives commonly encountered when using bivariate approaches to brain connectivity estimation. Additionally, the constituents of a number of brain subnetworks, and in particular of the central autonomic network (CAN), are still not completely determined. In this study we present and validate a global conditioning approach to reconstructing directed networks using complex synthetic networks of nonlinear oscillators. We then employ our framework, along with a probabilistic model for heartbeat generation, to characterize the directed functional connectome of the human brain and to establish which parts of this connectome effect the directed central modulation of peripheral autonomic cardiovascular control. We demonstrate the effectiveness of our conditioning approach and unveil a top-down directed influence of the default mode network on the salience network, which in turn is seen to be the strongest modulator of directed autonomic cardiovascular control.
机译：虽然大量的研究专注于脑内生理网络（即脑连接）以及与其疾病相关的像差的研究，但很少有调查员专注于估计这些脑大脑相互作用的方向性，这是鉴于复杂性的大脑网络，应适当调节，以避免在使用双重脑连接估计时常常遇到的大量误报。另外，许多脑子网的成分，特别是中央自主网络（CAN）的组成部分仍未完全确定。在这项研究中，我们展示并验证了使用非线性振荡器的复杂合成网络重建定向网络的全局调理方法。然后我们雇用我们的框架，以及心跳生成的概率模型，以表征人脑的定向功能连接，并建立这种连接的部分效果外周自主心血管控制的定向中心调制。我们展示了我们的调理方法的有效性，并揭示了默认模式网络对突出网络上的自上而下的指导影响，这反过来被视为定向自主心血管控制的最强调制器。

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