Riedl Valentin, Utz Lukas, Castrillón Gabriel, Grimmer Timo, Rauschecker Josef P, Ploner Markus, Friston Karl J, Drzezga Alexander, Sorg Christian
Department of Neuroradiology, Klinikum rechts der Isar, Technischen Universitaet Muenchen, 81675 Muenchen, Germany; Department of Nuclear Medicine, Klinikum rechts der Isar, Technischen Universitaet Muenchen, 81675 Muenchen, Germany; Neuroimaging Center, Klinikum Rechts der Isar, Technischen Universitaet Muenchen, 81675 Muenchen, Germany;
Department of Neuroradiology, Klinikum rechts der Isar, Technischen Universitaet Muenchen, 81675 Muenchen, Germany; Neuroimaging Center, Klinikum Rechts der Isar, Technischen Universitaet Muenchen, 81675 Muenchen, Germany; Institute of Advanced Studies, Technischen Universitaet Muenchen, 81675 Muenchen, Germany;
Proc Natl Acad Sci U S A. 2016 Jan 12;113(2):428-33. doi: 10.1073/pnas.1513752113. Epub 2015 Dec 28.
Directionality of signaling among brain regions provides essential information about human cognition and disease states. Assessing such effective connectivity (EC) across brain states using functional magnetic resonance imaging (fMRI) alone has proven difficult, however. We propose a novel measure of EC, termed metabolic connectivity mapping (MCM), that integrates undirected functional connectivity (FC) with local energy metabolism from fMRI and positron emission tomography (PET) data acquired simultaneously. This method is based on the concept that most energy required for neuronal communication is consumed postsynaptically, i.e., at the target neurons. We investigated MCM and possible changes in EC within the physiological range using "eyes open" versus "eyes closed" conditions in healthy subjects. Independent of condition, MCM reliably detected stable and bidirectional communication between early and higher visual regions. Moreover, we found stable top-down signaling from a frontoparietal network including frontal eye fields. In contrast, we found additional top-down signaling from all major clusters of the salience network to early visual cortex only in the eyes open condition. MCM revealed consistent bidirectional and unidirectional signaling across the entire cortex, along with prominent changes in network interactions across two simple brain states. We propose MCM as a novel approach for inferring EC from neuronal energy metabolism that is ideally suited to study signaling hierarchies in the brain and their defects in brain disorders.
脑区之间信号传导的方向性提供了有关人类认知和疾病状态的重要信息。然而，仅使用功能磁共振成像（fMRI）来评估跨脑状态的这种有效连接性（EC）已被证明是困难的。我们提出了一种新的EC测量方法，称为代谢连接性映射（MCM），它将无向功能连接性（FC）与同时从fMRI和正电子发射断层扫描（PET）数据中获取的局部能量代谢相结合。该方法基于这样的概念，即神经元通信所需的大部分能量是在突触后消耗的，即在靶神经元处。我们在健康受试者中使用“睁眼”与“闭眼”条件研究了MCM以及生理范围内EC的可能变化。与条件无关，MCM可靠地检测到早期和高级视觉区域之间稳定且双向的通信。此外，我们发现来自包括额叶眼区在内的额顶网络的稳定的自上而下的信号传导。相比之下，我们仅在睁眼条件下发现从显著性网络的所有主要簇到早期视觉皮层的额外的自上而下的信号传导。MCM揭示了整个皮层中一致的双向和单向信号传导，以及跨两种简单脑状态的网络相互作用的显著变化。我们提出MCM作为一种从神经元能量代谢推断EC的新方法，它非常适合研究大脑中的信号传导层次及其在脑部疾病中的缺陷。
