Mayhew S D, Bagshaw A P
Birmingham University Imaging Centre (BUIC), School of Psychology, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK.
Birmingham University Imaging Centre (BUIC), School of Psychology, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK.
Neuroimage. 2017 Jul 15;155:120-137. doi: 10.1016/j.neuroimage.2017.04.051. Epub 2017 Apr 25.
Accurate characterization of the spatiotemporal relationship between two of the most prominent neuroimaging measures of neuronal activity, the 8-13Hz, occipito-parietal EEG alpha oscillation and the BOLD fMRI signal, must encompass the intrinsically dynamic nature of both alpha power and brain function. Here, during the eyes-open resting state, we use a 16s sliding-window analysis and demonstrate that the mean spatial network of dynamic alpha-BOLD correlations is highly comparable to the static network calculated over six minutes. However, alpha-BOLD correlations showed substantial spatiotemporal variability within-subjects and passed through many different configurations such that the static network was fully represented in only ~10% of 16s epochs, with visual and parietal regions (coherent on average) often opposingly correlated with each other or with alpha. We find that the common assumption of static-alpha BOLD correlations greatly oversimplifies temporal variation in brain network dynamics. Fluctuations in alpha-BOLD coupling significantly depended upon the instantaneous amplitude of alpha power, and primary and lateral visual areas were most strongly negatively correlated with alpha during different alpha power states, possibly suggesting the action of multiple alpha mechanisms. Dynamic alpha-BOLD correlations could not be explained by eye-blinks/movements, head motion or non-neuronal physiological variability. Individual's mean alpha power and frequency were found to contribute to between-subject variability in alpha-BOLD correlations. Additionally, application to a visual stimulation dataset showed that dynamic alpha-BOLD correlations provided functional information pertaining to the brain's response to stimulation by exhibiting spatiotemporal fluctuations related to variability in the trial-by-trial BOLD response magnitude. Significantly weaker visual alpha-BOLD correlations were found both preceding and following small amplitude BOLD response trials compared to large response trials.
准确描述神经元活动的两种最突出的神经影像学测量指标之间的时空关系,即8 - 13Hz枕顶叶脑电图α振荡和血氧水平依赖性功能磁共振成像(BOLD fMRI)信号,必须考虑到α功率和脑功能固有的动态特性。在此,在睁眼静息状态下,我们使用16秒滑动窗口分析,并证明动态α - BOLD相关性的平均空间网络与在六分钟内计算出的静态网络高度可比。然而,α - BOLD相关性在个体内部表现出显著的时空变异性,并且经历了许多不同的配置,以至于静态网络仅在约10%的16秒时间段中得到充分体现,视觉和顶叶区域(平均而言是相干的)之间常常呈现相反的相关性,或者与α呈现相反的相关性。我们发现,关于静态α - BOLD相关性的常见假设极大地简化了脑网络动力学中的时间变化。α - BOLD耦合的波动显著依赖于α功率的瞬时幅度,并且在不同的α功率状态下,初级视觉区域和外侧视觉区域与α的负相关性最强,这可能暗示了多种α机制的作用。动态α - BOLD相关性无法用眼动/眨眼、头部运动或非神经元生理变异性来解释。研究发现个体的平均α功率和频率对个体间α - BOLD相关性的变异性有贡献。此外,将其应用于视觉刺激数据集表明,动态α - BOLD相关性通过展现与逐次试验的BOLD反应幅度变异性相关的时空波动,提供了与大脑对刺激的反应相关的功能信息。与大反应试验相比,在小幅度BOLD反应试验之前和之后发现视觉α - BOLD相关性明显较弱。