Brain and Mind Centre, The University of Sydney, Sydney, Australia.
Brain and Mind Centre, The University of Sydney, Sydney, Australia; Sydney School of Medicine, Central Clinical School, The University of Sydney, Australia.
Neuroimage. 2022 Oct 15;260:119455. doi: 10.1016/j.neuroimage.2022.119455. Epub 2022 Jul 7.
Complex cognitive abilities are thought to arise from the ability of the brain to adaptively reconfigure its internal network structure as a function of task demands. Recent work has suggested that this inherent flexibility may in part be conferred by the widespread projections of the ascending arousal systems. While the different components of the ascending arousal system are often studied in isolation, there are anatomical connections between neuromodulatory hubs that we hypothesise are crucial for mediating key features of adaptive network dynamics, such as the balance between integration and segregation. To test this hypothesis, we estimated the strength of structural connectivity between key hubs of the noradrenergic and cholinergic arousal systems (the locus coeruleus [LC] and nucleus basalis of Meynert [nbM], respectively). We then asked whether the strength of structural LC and nbM inter-connectivity was related to individual differences in the emergent, dynamical signatures of functional integration measured from resting state fMRI data, such as network and attractor topography. We observed a significant positive relationship between the strength of white-matter connections between the LC and nbM and the extent of network-level integration following BOLD signal peaks in LC relative to nbM activity. In addition, individuals with denser white-matter streamlines interconnecting neuromodulatory hubs also demonstrated a heightened ability to shift to novel brain states. These results suggest that individuals with stronger structural connectivity between the noradrenergic and cholinergic systems have a greater capacity to mediate the flexible network dynamics required to support complex, adaptive behaviour. Furthermore, our results highlight the underlying static features of the neuromodulatory hubs can impose some constraints on the dynamic features of the brain.
复杂的认知能力被认为源于大脑根据任务需求自适应地重新配置其内部网络结构的能力。最近的研究表明，这种固有灵活性可能部分归因于上行唤醒系统的广泛投射。虽然上行唤醒系统的不同组成部分通常是孤立地进行研究的，但在神经调质中枢之间存在解剖学连接，我们假设这些连接对于调节自适应网络动态的关键特征（例如整合与分离之间的平衡）至关重要。为了验证这一假设，我们估计了去甲肾上腺素能和胆碱能唤醒系统（蓝斑核 [LC] 和基底前脑核 [nbM]）的关键枢纽之间结构连接的强度。然后，我们询问 LC 和 nbM 之间结构互连的强度是否与从静息态 fMRI 数据测量的功能整合的涌现、动态特征的个体差异有关，例如网络和吸引子拓扑。我们观察到 LC 与 nbM 之间的白质连接强度与 LC 相对于 nbM 活动的 BOLD 信号峰值后的网络水平整合程度之间存在显著正相关。此外，连接神经调质中枢的白质流线更密集的个体也表现出更高的能力来转变为新的大脑状态。这些结果表明，去甲肾上腺素能和胆碱能系统之间结构连接更强的个体具有更大的能力来调节支持复杂、适应性行为所需的灵活网络动态。此外，我们的结果强调了神经调质中枢的基础静态特征可以对大脑的动态特征施加一些限制。
