Davey Catherine E, Grayden David B, Johnston Leigh A
Department of Biomedical Engineering, University of Melbourne, Melbourne, VIC, Australia.
Melbourne Brain Centre Imaging Unit, University of Melbourne, Melbourne, VIC, Australia.
Front Neurosci. 2021 Feb 24;15:574979. doi: 10.3389/fnins.2021.574979. eCollection 2021.
In this work fMRI BOLD datasets are shown to contain slice-dependent non-stationarities. A model containing slice-dependent, non-stationary signal power is proposed to address time-varying signal power during BOLD data acquisition. The impact of non-stationary power on functional MRI connectivity is analytically derived, establishing that pairwise connectivity estimates are scaled by a function of the time-varying signal power, with magnitude upper bound by 1, and that the variance of sample correlation is increased, thereby inducing spurious connectivity. Consequently, we make the observation that time-varying power during acquisition of BOLD timeseries has the propensity to diminish connectivity estimates. To ameliorate the impact of non-stationary signal power, a simple correction for slice-dependent non-stationarity is proposed. Our correction is analytically shown to restore both signal stationarity and, subsequently, the integrity of connectivity estimates. Theoretical results are corroborated with empirical evidence demonstrating the utility of our correction. In addition, slice-dependent non-stationary variance is experimentally determined to be optimally characterized by an inverse Gamma distribution. The resulting distribution of a voxel's signal intensity is analytically derived to be a generalized Student's- distribution, providing support for the Gaussianity assumption typically imposed by fMRI connectivity methods.
在这项工作中，功能磁共振成像血氧水平依赖（fMRI BOLD）数据集被证明包含与切片相关的非平稳性。提出了一个包含与切片相关的非平稳信号功率的模型，以解决BOLD数据采集期间随时间变化的信号功率问题。通过分析得出了非平稳功率对功能磁共振成像连接性的影响，确定成对连接性估计值按随时间变化的信号功率的函数进行缩放，幅度上限为1，并且样本相关性的方差增加，从而导致虚假连接性。因此，我们观察到在采集BOLD时间序列期间随时间变化的功率有降低连接性估计值的倾向。为了减轻非平稳信号功率的影响，提出了一种针对与切片相关的非平稳性的简单校正方法。我们的校正方法经分析表明既能恢复信号的平稳性，随后又能恢复连接性估计值的完整性。理论结果得到了经验证据的证实，证明了我们校正方法的实用性。此外，通过实验确定与切片相关的非平稳方差以逆伽马分布进行最佳表征。经分析得出体素信号强度的结果分布为广义学生分布，为功能磁共振成像连接性方法通常采用的高斯假设提供了支持。
