静息和睡眠状态下大脑功能连接的研究:一项近红外光谱学研究。
Exploring brain functional connectivity in rest and sleep states: a fNIRS study.
机构信息
Gwangju Institute of Science and Technology, Department of Biomedical Science and Engineering, 123 Cheomdan-gwagiro, Buk-gu, Gwangju, 61005, Korea.
University of Texas at Arlington, Department of Bioengineering, 500 UTA Blvd, Arlington, Texas, 76019, United States.
出版信息
Sci Rep. 2018 Nov 1;8(1):16144. doi: 10.1038/s41598-018-33439-2.
This study investigates the brain functional connectivity in the rest and sleep states. We collected EEG, EOG, and fNIRS signals simultaneously during rest and sleep phases. The rest phase was defined as a quiet wake-eyes open (w_o) state, while the sleep phase was separated into three states; quiet wake-eyes closed (w_c), non-rapid eye movement sleep stage 1 (N1), and non-rapid eye movement sleep stage 2 (N2) using the EEG and EOG signals. The fNIRS signals were used to calculate the cerebral hemodynamic responses (oxy-, deoxy-, and total hemoglobin). We grouped 133 fNIRS channels into five brain regions (frontal, motor, temporal, somatosensory, and visual areas). These five regions were then used to form fifteen brain networks. A network connectivity was computed by calculating the Pearson correlation coefficients of the hemodynamic responses between fNIRS channels belonging to the network. The fifteen networks were compared across the states using the connection ratio and connection strength calculated from the normalized correlation coefficients. Across all fifteen networks and three hemoglobin types, the connection ratio was high in the w_c and N1 states and low in the w_o and N2 states. In addition, the connection strength was similar between the w_c and N1 states and lower in the w_o and N2 states. Based on our experimental results, we believe that fNIRS has a high potential to be a main tool to study the brain connectivity in the rest and sleep states.
本研究调查了静息和睡眠状态下的大脑功能连接。我们在静息和睡眠阶段同时采集了 EEG、EOG 和 fNIRS 信号。静息期被定义为安静清醒睁眼(w_o)状态,而睡眠期则使用 EEG 和 EOG 信号分为三个状态:安静清醒闭眼(w_c)、非快速眼动睡眠 1 期(N1)和非快速眼动睡眠 2 期(N2)。fNIRS 信号用于计算脑血流动力学反应(氧合、脱氧和总血红蛋白)。我们将 133 个 fNIRS 通道分为五个脑区(额区、运动区、颞区、体感区和视觉区)。然后,这五个区域被用来形成十五个脑网络。通过计算属于网络的 fNIRS 通道之间的血流动力学反应的 Pearson 相关系数来计算网络连接。使用归一化相关系数计算的连接比和连接强度来比较十五个网络在不同状态下的差异。在所有十五个网络和三种血红蛋白类型中,连接比在 w_c 和 N1 状态下较高,在 w_o 和 N2 状态下较低。此外,连接强度在 w_c 和 N1 状态下相似,在 w_o 和 N2 状态下较低。基于我们的实验结果,我们认为 fNIRS 很有潜力成为研究静息和睡眠状态下大脑连接的主要工具。