Bukhari Qasim, Schroeter Aileen, Cole David M, Rudin Markus
Institute of Biomedical Engineering, University of Zurich and ETH Zurich Zurich, Switzerland.
Institute of Biomedical Engineering, University of Zurich and ETH ZurichZurich, Switzerland; Department of Psychiatry, Psychotherapy and Psychosomatics, University Hospital of PsychiatryZurich, Switzerland.
Front Neural Circuits. 2017 Feb 3;11:5. doi: 10.3389/fncir.2017.00005. eCollection 2017.
fMRI studies in mice typically require the use of anesthetics. Yet, it is known that anesthesia alters responses to stimuli or functional networks at rest. In this work, we have used Dual Regression analysis Network Modeling to investigate the effects of two commonly used anesthetics, isoflurane and medetomidine, on rs-fMRI derived functional networks, and in particular to what extent anesthesia affected the interaction within and between these networks. Experimental data have been used from a previous study (Grandjean et al., 2014). We applied multivariate ICA analysis and Dual Regression to infer the differences in functional connectivity between isoflurane- and medetomidine-anesthetized mice. Further network analysis was performed to investigate within- and between-network connectivity differences between these anesthetic regimens. The results revealed five major networks in the mouse brain: lateral cortical, associative cortical, default mode, subcortical, and thalamic network. The anesthesia regime had a profound effect both on within- and between-network interactions. Under isoflurane anesthesia predominantly intra- and inter-cortical interactions have been observed, with only minor interactions involving subcortical structures and in particular attenuated cortico-thalamic connectivity. In contrast, medetomidine-anesthetized mice displayed subcortical functional connectivity including interactions between cortical and thalamic ICA components. Combining the two anesthetics at low dose resulted in network interaction that constituted the superposition of the interaction observed for each anesthetic alone. The study demonstrated that network modeling is a promising tool for analyzing the brain functional architecture in mice and comparing alterations therein caused by different physiological or pathological states. Understanding the differential effects of anesthetics on brain networks and their interaction is essential when interpreting fMRI data recorded under specific physiological and pathological conditions.
在小鼠中进行功能磁共振成像(fMRI)研究通常需要使用麻醉剂。然而,众所周知,麻醉会改变对刺激的反应或静息状态下的功能网络。在这项研究中,我们使用双回归分析网络建模来研究两种常用麻醉剂异氟烷和美托咪定对基于静息态功能磁共振成像(rs-fMRI)得出的功能网络的影响,特别是麻醉在多大程度上影响了这些网络内部以及之间的相互作用。实验数据来自之前的一项研究(格兰德让等人,2014年)。我们应用多变量独立成分分析(ICA)和双回归来推断异氟烷麻醉小鼠和美托咪定麻醉小鼠之间功能连接性的差异。进一步进行网络分析以研究这些麻醉方案在网络内部和网络之间的连接性差异。结果揭示了小鼠大脑中的五个主要网络:外侧皮质网络、联合皮质网络、默认模式网络、皮质下网络和丘脑网络。麻醉方案对网络内部和网络之间的相互作用都有深远影响。在异氟烷麻醉下,主要观察到皮质内和皮质间的相互作用,只有涉及皮质下结构的轻微相互作用,特别是皮质 - 丘脑连接性减弱。相比之下,美托咪定麻醉的小鼠表现出皮质下功能连接性,包括皮质和丘脑ICA成分之间的相互作用。低剂量联合使用这两种麻醉剂会导致网络相互作用,这种相互作用构成了单独使用每种麻醉剂时观察到的相互作用的叠加。该研究表明,网络建模是分析小鼠大脑功能结构以及比较不同生理或病理状态引起的大脑功能结构变化的一种很有前景的工具。在解释特定生理和病理条件下记录的fMRI数据时,了解麻醉剂对脑网络及其相互作用的不同影响至关重要。