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一种用于神经血管耦合定量床边监测的新技术。

A novel technique for quantitative bedside monitoring of neurovascular coupling.

作者信息

Govindan R B, Massaro An, Chang Taeun, Vezina Gilbert, du Plessis Adré

机构信息

Division of Fetal and Transitional Medicine, Fetal Medicine Institute, Children's National Health System, 111 Michigan Ave NW, Washington, DC 20010, USA.

Division of Neonatology, Children's National, 111 Michigan Ave NW, Washington, DC 20010, USA.

出版信息

J Neurosci Methods. 2016 Feb 1;259:135-142. doi: 10.1016/j.jneumeth.2015.11.025. Epub 2015 Dec 10.

Abstract

BACKGROUND

There is no current method for continuous quantification of neurovascular coupling (NVC) in spontaneous brain activity. To fill this void, we propose a novel method to quantify NVC using electroencephalogram (EEG) and near-infrared spectroscopy (NIRS) data.

NEW METHOD

Since EEG and NIRS measure physiologic changes occurring at different time scales, we bring them into a common dynamical time frame (DTF). To achieve this, we partition both signals into one-second epochs and calculate the standard deviation of the EEG and the average value of the NIRS for each epoch. We then quantify the NVC by calculating spectral coherence between the two signals in the DTF. The resulting NVC will have a low resolution with all of its content localized below 1Hz.

RESULTS

After validating this framework on simulated data, we applied this approach to EEG and NIRS signals collected from four term infants undergoing therapeutic hypothermia for neonatal encephalopathy. Two of these infants showed no evidence of structural brain injury, and the other two died during the course of the therapy. The intact survivors showed emergence of NVC during hypothermia and/or after rewarming. In contrast, the two critically ill infants, who subsequently died, lacked this feature.

COMPARISON WITH EXISTING METHODS

Existing methods quantify NVC by averaging neurovascular signals based on certain events (for example seizure) in the EEG activity, whereas our approach quantifies coupling between spontaneous background EEG and NIRS.

CONCLUSION

Real-time continuous monitoring of NVC may be a promising physiologic signal for cerebral monitoring in future.

摘要

背景

目前尚无用于连续定量自发脑活动中神经血管耦合(NVC)的方法。为填补这一空白,我们提出一种利用脑电图(EEG)和近红外光谱(NIRS)数据定量NVC的新方法。

新方法

由于EEG和NIRS测量的是在不同时间尺度上发生的生理变化,我们将它们纳入一个共同的动态时间框架(DTF)。为实现这一点,我们将两个信号都划分为1秒的时段,并计算每个时段EEG的标准差和NIRS的平均值。然后,我们通过计算DTF中两个信号之间的频谱相干性来定量NVC。所得的NVC分辨率较低,其所有内容都集中在1Hz以下。

结果

在对模拟数据验证了该框架后,我们将这种方法应用于从4名因新生儿脑病接受治疗性低温的足月儿收集的EEG和NIRS信号。其中两名婴儿没有脑结构损伤的证据,另外两名在治疗过程中死亡。存活的婴儿在低温期间和/或复温后出现了NVC。相比之下,随后死亡的两名重症婴儿缺乏这一特征。

与现有方法的比较

现有方法通过基于EEG活动中的某些事件(例如癫痫发作)对神经血管信号进行平均来定量NVC,而我们的方法则是定量自发背景EEG和NIRS之间的耦合。

结论

NVC的实时连续监测可能是未来用于脑监测有前景的生理信号。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b234/7040446/c93440a40375/nihms743909f1.jpg

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