Department of Functional Brain Imaging, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan.
Neuroimage. 2012 Mar;60(1):738-46. doi: 10.1016/j.neuroimage.2011.12.082. Epub 2012 Jan 8.
The simultaneous recordings of neuronal and hemodynamic signals have revealed a significant involvement of high frequency bands (e.g., gamma range, 25-70 Hz) in neurovascular coupling. However, the dependence on a physiological parameter is unknown. In this study, we performed simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) recordings in 12 Wistar rats using a conventional forepaw stimulation paradigm and concurrently monitored the systemic physiological parameters of the partial pressure of arterial oxygen, partial pressure of arterial carbon dioxide, pH, mean arterial blood pressure, and heart rate through the rat femoral artery. The high frequency bands in the artifact-free EEG signals, especially those in the gamma range, demonstrated a maximum correlation with fMRI signals in the rat somatosensory cortex. A multiple linear regression analysis demonstrated that the correlation coefficient between the gamma power and fMRI signal depended on the actual values of the physiological parameters (R(2)=0.20, p<0.05), whereas the gamma power and fMRI signal by itself were independent. Among the parameters, the heart rate had a statistically significant slope (95% CI: 0.00027-0.0016, p<0.01) in a multiple linear regression model. These results indicate that neurovascular coupling is mainly driven by gamma oscillations, as expected, but coupling or potential decoupling is strongly influenced by systemic physiological parameters, which dynamically reflect the baseline vital status of the subject.
同时记录神经元和血液动力学信号揭示了高频带（例如，伽马范围，25-70 Hz）在神经血管耦合中的重要作用。然而，其对生理参数的依赖性尚不清楚。在这项研究中，我们使用传统的前爪刺激范式在 12 只 Wistar 大鼠中同时进行脑电图（EEG）和功能磁共振成像（fMRI）记录，并通过大鼠股动脉同时监测动脉血氧分压、动脉二氧化碳分压、pH 值、平均动脉血压和心率等系统生理参数。在无伪迹的 EEG 信号中的高频带，特别是伽马范围内的高频带，与大鼠体感皮层中的 fMRI 信号表现出最大相关性。多元线性回归分析表明，伽马功率与 fMRI 信号之间的相关系数取决于生理参数的实际值（R²=0.20，p<0.05），而伽马功率和 fMRI 信号本身是独立的。在这些参数中，心率在多元线性回归模型中具有统计学意义的斜率（95%置信区间：0.00027-0.0016，p<0.01）。这些结果表明，神经血管耦合主要由伽马振荡驱动，这是预期的，但耦合或潜在的去耦合强烈受到全身生理参数的影响，这些参数动态反映了主体的基本生命状态。
