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功能连接性和脑血流量的多模态分析揭示了丙泊酚在大规模脑网络中的共同和独特作用。

Multi-modal analysis of functional connectivity and cerebral blood flow reveals shared and unique effects of propofol in large-scale brain networks.

作者信息

Qiu Maolin, Scheinost Dustin, Ramani Ramachandran, Constable R Todd

机构信息

Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT 06520, USA.

Anesthesiology, Yale School of Medicine, New Haven, CT 06520, USA.

出版信息

Neuroimage. 2017 Mar 1;148:130-140. doi: 10.1016/j.neuroimage.2016.12.080. Epub 2017 Jan 6.

Abstract

Anesthesia-induced changes in functional connectivity and cerebral blow flow (CBF) in large-scale brain networks have emerged as key markers of reduced consciousness. However, studies of functional connectivity disagree on which large-scale networks are altered or preserved during anesthesia, making it difficult to find a consensus amount studies. Additionally, pharmacological alterations in CBF could amplify or occlude changes in connectivity due to the shared variance between CBF and connectivity. Here, we used data-driven connectivity methods and multi-modal imaging to investigate shared and unique neural correlates of reduced consciousness for connectivity in large-scale brain networks. Rs-fMRI and CBF data were collected from the same subjects during an awake and deep sedation condition induced by propofol. We measured whole-brain connectivity using the intrinsic connectivity distribution (ICD), a method not reliant on pre-defined seed regions, networks of interest, or connectivity thresholds. The shared and unique variance between connectivity and CBF were investigated. Finally, to account for shared variance, we present a novel extension to ICD that incorporates cerebral blood flow (CBF) as a scaling factor in the calculation of global connectivity, labeled CBF-adjusted ICD). We observed altered connectivity in multiple large-scale brain networks including the default mode (DMN), salience, visual, and motor networks and reduced CBF in the DMN, frontoparietal network, and thalamus. Regional connectivity and CBF were significantly correlated during both the awake and propofol condition. Nevertheless changes in connectivity and CBF between the awake and deep sedation condition were only significantly correlated in a subsystem of the DMN, suggesting that, while there is significant shared variance between the modalities, changes due to propofol are relatively unique. Similar, but less significant, results were observed in the CBF-adjusted ICD analysis, providing additional evidence that connectivity differences were not fully explained by CBF. In conclusion, these results provide further evidence of alterations in large-scale brain networks are associated with reduced consciousness and suggest that different modalities capture unique aspects of these large scale changes.

摘要

麻醉引起的大规模脑网络功能连接性和脑血流量(CBF)变化已成为意识降低的关键标志。然而,关于哪些大规模网络在麻醉期间发生改变或保持不变,功能连接性研究存在分歧,这使得难以在研究中达成共识。此外,由于CBF与连接性之间存在共同变化,CBF的药理学改变可能会放大或掩盖连接性的变化。在这里,我们使用数据驱动的连接性方法和多模态成像来研究大规模脑网络中连接性降低的意识的共同和独特神经关联。在由丙泊酚诱导的清醒和深度镇静状态下,从同一受试者收集静息态功能磁共振成像(Rs-fMRI)和CBF数据。我们使用内在连接性分布(ICD)测量全脑连接性,这是一种不依赖于预定义种子区域、感兴趣网络或连接性阈值的方法。研究了连接性和CBF之间的共同和独特变化。最后,为了解释共同变化,我们提出了ICD的一种新扩展,即在计算全局连接性时将脑血流量(CBF)作为缩放因子,标记为CBF调整后的ICD。我们观察到多个大规模脑网络的连接性发生改变,包括默认模式网络(DMN)、突显网络、视觉网络和运动网络,并且DMN、额顶叶网络和丘脑中的CBF降低。在清醒和丙泊酚状态下,区域连接性和CBF均显著相关。然而,清醒和深度镇静状态之间连接性和CBF的变化仅在DMN的一个子系统中显著相关,这表明,虽然这些模态之间存在显著的共同变化,但丙泊酚引起的变化相对独特。在CBF调整后的ICD分析中观察到类似但不太显著的结果,提供了额外证据表明连接性差异不能完全由CBF解释。总之,这些结果进一步证明了大规模脑网络的改变与意识降低有关,并表明不同模态捕捉了这些大规模变化的独特方面。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f9d3/5410383/8c733e4cad48/nihms860697f1.jpg

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