Bootstrap resampling method to estimate confidence intervals of activation-induced CBF changes using laser Doppler imaging.
Bootstrap resampling method to estimate confidence intervals of activation-induced CBF changes using laser Doppler imaging.
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Bootstrap 重采样方法使用激光多普勒成像估计激活引起的 CBF 变化的置信区间。
DOI：
10.1016/j.jneumeth.2005.01.021
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发表时间：
2005
期刊：
影响因子：
--
通讯作者：
Biswal,BharatB
中科院分区：
文献类型：
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作者：
Kannurpatti,SridharS;Biswal,BharatB
激光多谱勒成像(LDI)的信号和噪声特征可能会因基础血管口径的不同而显著不同。此外，在典型的实验中，噪声特性不是随时间变化的(非平稳的)，并且可能在静止和激活条件下变化。由于一次只能采集有限数量的图像，因此需要连接来自类似实验的数据，这可能会由于仪器响应而导致时间噪声的进一步变化。在诸如互相关的传统统计分析方法中，通常使用固定的显著阈值(对于整个图像)来检测激活，假设噪声随时间和正态分布是恒定的。因此，由于基线Ld噪声的时间差异，统计显著性可能变强或变弱，这可能偏离正态分布。这项研究的主要重点是应用Bootstrap重采样与互相关相结合的方法来逐个像素地估计可信区间，以避免分布规格的附加测量误差导致可靠的晶须激活引起的CBF变化。在95%的置信度水平下，与传统的互相关相比，在相关系数分布的置信度区间之后的自举重采样使活动像素的数量增加了近45%。这些像素大多局限于基线LD流量中等和较大的区域，与正常值有相当大的偏差。这表明，Bootstrap估计的置信度区间可以无偏地检测大脑皮质的CBF变化，特别是在噪声时间变化较大和CNR较低的区域。
Laser Doppler imaging (LDI) signal and noise characteristics can vary significantly depending upon the underlying vascular caliber. Further, noise characteristics are not constant over time (non-stationary) and can vary during resting and activated conditions in a typical experiment. Since only a limited number of images can be acquired in a single run, concatenation of data from similar experimental trials becomes necessary which can induce further variation in temporal noise due to instrumental response. In conventional statistical analysis methods such as cross-correlation, a fixed significance threshold is generally used (for the entire image) to detect activation assuming constant noise over time and a normal distribution. As a consequence, statistical significance can become strong or weak due to temporal differences in baseline LD noise, which can possibly deviate from a normal distribution. The main emphasis of this study was the application of bootstrap resampling in conjunction with cross-correlation to estimate the confidence intervals on a pixel-by-pixel basis to avoid distributional specifications on the additive measurement error leading to reliable whisker activation-induced CBF changes. At a 95% confidence level, bootstrap resampling followed by confidence intervals for the correlation coefficient distribution increased the number of active pixels by almost 45% when compared to conventional cross-correlation. These pixels were mostly confined to areas with intermediate and large baseline LD flux with considerable deviation from normality. It is suggested that confidence intervals of the bootstrap estimates can lead to unbiased detection of CBF change in the cerebral cortex, particularly in regions with large temporal variation in noise and low CNR.