Zarahn E, Aguirre G K, D'Esposito M
Department of Neurology, University of Pennsylvania Medical Center, Philadelphia 19104-4283, USA.
Neuroimage. 1997 Apr;5(3):179-97. doi: 10.1006/nimg.1997.0263.
Temporal autocorrelation, spatial coherency, and their effects on voxel-wise parametric statistics were examined in BOLD fMRI null-hypothesis, or "noise," datasets. Seventeen normal, young subjects were scanned using BOLD fMRI while not performing any time-locked experimental behavior. Temporal autocorrelation in these datasets was described well by a 1/frequency relationship. Voxel-wise statistical analysis of these noise datasets which assumed independence (i.e., ignored temporal autocorrelation) rejected the null hypothesis at a higher rate than specified by the nominal alpha. Temporal smoothing in conjunction with the use of a modified general linear model (Worsley and Friston, 1995, NeuroImage 2: 173-182) brought the false-positive rate closer to the nominal alpha. It was also found that the noise fMRI datasets contain spatially coherent time signals. This observed spatial coherence could not be fully explained by a continuously differentiable spatial autocovariance function and was much greater for lower temporal frequencies. Its presence made voxel-wise test statistics in a given noise dataset dependent, and thus shifted their distributions to the right or left of 0. Inclusion of a "global signal" covariate in the general linear model reduced this dependence and consequently stabilized (i.e., reduced the variance of) dataset false-positive rates.
在BOLD功能磁共振成像（fMRI）的零假设或“噪声”数据集中，研究了时间自相关、空间相干性及其对体素参数统计的影响。对17名正常年轻受试者进行了BOLD fMRI扫描，期间他们未执行任何时间锁定的实验行为。这些数据集中的时间自相关通过1/频率关系得到了很好的描述。对这些假设独立（即忽略时间自相关）的噪声数据集进行体素统计分析时，零假设被拒绝的比例高于名义α水平所指定的比例。结合使用改进的一般线性模型（Worsley和Friston，1995年，《神经影像学》2：173 - 182）进行时间平滑处理，使假阳性率更接近名义α水平。还发现噪声fMRI数据集包含空间相干的时间信号。这种观察到的空间相干性不能通过连续可微的空间自协方差函数得到充分解释，并且对于较低时间频率而言其程度要大得多。它的存在使得给定噪声数据集中的体素测试统计量具有依赖性，从而将其分布向右或向左偏离0。在一般线性模型中纳入“全局信号”协变量可减少这种依赖性，进而稳定（即降低）数据集的假阳性率。
