Duggento Andrea, Bianciardi Marta, Passamonti Luca, Wald Lawrence L, Guerrisi Maria, Barbieri Riccardo, Toschi Nicola
Medical Physics Section, Department of Biomedicine and Prevention, University of Rome 'Tor Vergata', Rome, Italy
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA.
Philos Trans A Math Phys Eng Sci. 2016 May 13;374(2067). doi: 10.1098/rsta.2015.0185.
The causal, directed interactions between brain regions at rest (brain-brain networks) and between resting-state brain activity and autonomic nervous system (ANS) outflow (brain-heart links) have not been completely elucidated. We collected 7 T resting-state functional magnetic resonance imaging (fMRI) data with simultaneous respiration and heartbeat recordings in nine healthy volunteers to investigate (i) the causal interactions between cortical and subcortical brain regions at rest and (ii) the causal interactions between resting-state brain activity and the ANS as quantified through a probabilistic, point-process-based heartbeat model which generates dynamical estimates for sympathetic and parasympathetic activity as well as sympathovagal balance. Given the high amount of information shared between brain-derived signals, we compared the results of traditional bivariate Granger causality (GC) with a globally conditioned approach which evaluated the additional influence of each brain region on the causal target while factoring out effects concomitantly mediated by other brain regions. The bivariate approach resulted in a large number of possibly spurious causal brain-brain links, while, using the globally conditioned approach, we demonstrated the existence of significant selective causal links between cortical/subcortical brain regions and sympathetic and parasympathetic modulation as well as sympathovagal balance. In particular, we demonstrated a causal role of the amygdala, hypothalamus, brainstem and, among others, medial, middle and superior frontal gyri, superior temporal pole, paracentral lobule and cerebellar regions in modulating the so-called central autonomic network (CAN). In summary, we show that, provided proper conditioning is employed to eliminate spurious causalities, ultra-high-field functional imaging coupled with physiological signal acquisition and GC analysis is able to quantify directed brain-brain and brain-heart interactions reflecting central modulation of ANS outflow.
静息状态下脑区之间（脑-脑网络）以及静息态脑活动与自主神经系统（ANS）输出之间（脑-心连接）的因果性、定向相互作用尚未完全阐明。我们收集了9名健康志愿者的7T静息态功能磁共振成像（fMRI）数据，并同步记录呼吸和心跳，以研究（i）静息状态下皮质和皮质下脑区之间的因果相互作用，以及（ii）静息态脑活动与ANS之间的因果相互作用，这种相互作用通过基于概率点过程的心跳模型进行量化，该模型可生成交感神经和副交感神经活动以及交感-迷走平衡的动态估计值。鉴于脑源性信号之间共享大量信息，我们将传统双变量格兰杰因果关系（GC）的结果与一种全局条件方法进行了比较，该方法评估了每个脑区对因果目标的额外影响，同时排除了其他脑区同时介导的影响。双变量方法导致大量可能虚假的因果脑-脑连接，而使用全局条件方法，我们证明了皮质/皮质下脑区与交感神经和副交感神经调制以及交感-迷走平衡之间存在显著的选择性因果连接。特别是，我们证明了杏仁核、下丘脑、脑干以及内侧、中间和额上回、颞上极、中央旁小叶和小脑区域在调节所谓的中枢自主网络（CAN）中的因果作用。总之，我们表明，只要采用适当的条件来消除虚假因果关系，超高场功能成像结合生理信号采集和GC分析就能够量化反映ANS输出中枢调制的定向脑-脑和脑-心相互作用。
