Amico Enrico, Gomez Francisco, Di Perri Carol, Vanhaudenhuyse Audrey, Lesenfants Damien, Boveroux Pierre, Bonhomme Vincent, Brichant Jean-François, Marinazzo Daniele, Laureys Steven
Coma Science Group, Cyclotron Research Centre, University of Liège, Liège, Belgium; Faculty of Psychology and Educational Sciences, Department of Data Analysis, Ghent University, Ghent, Belgium.
Coma Science Group, Cyclotron Research Centre, University of Liège, Liège, Belgium.
PLoS One. 2014 Jun 30;9(6):e100012. doi: 10.1371/journal.pone.0100012. eCollection 2014.
Recent studies have been shown that functional connectivity of cerebral areas is not a static phenomenon, but exhibits spontaneous fluctuations over time. There is evidence that fluctuating connectivity is an intrinsic phenomenon of brain dynamics that persists during anesthesia. Lately, point process analysis applied on functional data has revealed that much of the information regarding brain connectivity is contained in a fraction of critical time points of a resting state dataset. In the present study we want to extend this methodology for the investigation of resting state fMRI spatial pattern changes during propofol-induced modulation of consciousness, with the aim of extracting new insights on brain networks consciousness-dependent fluctuations.
Resting-state fMRI volumes on 18 healthy subjects were acquired in four clinical states during propofol injection: wakefulness, sedation, unconsciousness, and recovery. The dataset was reduced to a spatio-temporal point process by selecting time points in the Posterior Cingulate Cortex (PCC) at which the signal is higher than a given threshold (i.e., BOLD intensity above 1 standard deviation). Spatial clustering on the PCC time frames extracted was then performed (number of clusters = 8), to obtain 8 different PCC co-activation patterns (CAPs) for each level of consciousness.
The current analysis shows that the core of the PCC-CAPs throughout consciousness modulation seems to be preserved. Nonetheless, this methodology enables to differentiate region-specific propofol-induced reductions in PCC-CAPs, some of them already present in the functional connectivity literature (e.g., disconnections of the prefrontal cortex, thalamus, auditory cortex), some others new (e.g., reduced co-activation in motor cortex and visual area).
In conclusion, our results indicate that the employed methodology can help in improving and refining the characterization of local functional changes in the brain associated to propofol-induced modulation of consciousness.
最近的研究表明,脑区的功能连接并非静态现象,而是随时间呈现出自发波动。有证据表明,波动连接是脑动力学的一种内在现象,在麻醉期间持续存在。最近,应用于功能数据的点过程分析表明,关于脑连接的许多信息包含在静息态数据集的一小部分关键时间点中。在本研究中,我们希望扩展这种方法,以研究丙泊酚诱导意识调节期间静息态功能磁共振成像(fMRI)空间模式的变化,目的是提取关于脑网络意识依赖性波动的新见解。
在丙泊酚注射的四种临床状态下,采集了18名健康受试者静息态fMRI数据:清醒、镇静、无意识和恢复。通过选择后扣带回皮质(PCC)中信号高于给定阈值(即血氧水平依赖(BOLD)强度高于1个标准差)的时间点,将数据集简化为时空点过程。然后对提取的PCC时间帧进行空间聚类(聚类数 = 8),以获得每个意识水平的8种不同的PCC共激活模式(CAPs)。
当前分析表明,在整个意识调节过程中,PCC-CAPs的核心似乎得以保留。尽管如此,这种方法能够区分丙泊酚诱导的PCC-CAPs区域特异性减少,其中一些已经在功能连接文献中出现(例如,前额叶皮质、丘脑、听觉皮质的断开连接),其他一些则是新发现的(例如,运动皮质和视觉区域的共激活减少)。
总之,我们的结果表明,所采用的方法有助于改进和完善与丙泊酚诱导意识调节相关的脑局部功能变化的特征描述。