Gillihan Seth J, Detre John A, Farah Martha J, Rao Hengyi
Center for Cognitive Neuroscience, University of Pennsylvania.
Center for Cognitive Neuroscience, University of Pennsylvania ; Center for Functional Neuroimaging, University of Pennsylvania.
J Cogn Sci (Seoul). 2011 Apr;12(2):195-210. doi: 10.17791/jcs.2011.12.2.195.
Daily variations in weather are known to be associated with variations in mood. However, little is known about the specific brain regions that instantiate weather-related mood changes. We used a data-driven approach and ASL perfusion fMRI to assess the neural substrates associated with weather-induced mood variability. The data-driven approach was conducted with mood ratings under various weather conditions (N = 464). Forward stepwise regression was conducted to develop a statistical model of mood as a function of weather conditions. The model results were used to calculate the mood-relevant weather index which served as the covariate in the regression analysis of the resting CBF (N = 42) measured by ASL perfusion fMRI under various weather conditions. The resting CBF activities in the left insula-prefrontal cortex and left superior parietal lobe were negatively correlated (corrected p<0.05) with the weather index, indicating that better mood-relevant weather conditions were associated with lower CBF in these regions within the brain's emotional network. The present study represents a first step toward the investigation of the effect of natural environment on baseline human brain function, and suggests the feasibility of ASL perfusion fMRI for such study.
众所周知，天气的日常变化与情绪变化有关。然而，对于体现与天气相关情绪变化的具体脑区，我们却知之甚少。我们采用数据驱动方法和动脉自旋标记灌注功能磁共振成像（ASL灌注fMRI）来评估与天气诱发的情绪变异性相关的神经基质。数据驱动方法是在各种天气条件下进行情绪评分（N = 464）。进行向前逐步回归以建立作为天气条件函数的情绪统计模型。模型结果用于计算与情绪相关的天气指数，该指数在各种天气条件下通过ASL灌注fMRI测量静息脑血流量（CBF，N = 42）的回归分析中用作协变量。左脑岛-前额叶皮层和左上顶叶的静息CBF活动与天气指数呈负相关（校正p<0.05），表明在大脑情绪网络中，与情绪相关的更好天气条件与这些区域较低的CBF相关。本研究是朝着调查自然环境对人类基线脑功能影响迈出的第一步，并表明ASL灌注fMRI用于此类研究的可行性。
