Serences John T
Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD 21218, USA.
Neuroimage. 2004 Apr;21(4):1690-700. doi: 10.1016/j.neuroimage.2003.12.021.
Information about the shape and temporal duration of the blood oxygenation level dependent (BOLD) response can inform both functional neuroanatomy and psychological theory. However, the BOLD response evolves over 20 s or more, making it difficult to distinguish the unique characteristics of the response evoked by temporally adjacent stimuli. Fortunately, event-related BOLD signals can be extracted given that there is adequate variance in the distribution of inter-stimulus intervals (ISI). Unfortunately, the ISI distribution that yields the highest statistical efficiency is not always optimal from a psychological perspective; variability in the stimulus timing may complicate the interpretation of neuroimaging data in terms of underlying cognitive operations. In the present paper, Monte Carlo simulations are used to evaluate two techniques for estimating the event-related BOLD timeseries-event-related averaging and deconvolution using the Ordinary Least Squares estimate -with respect to maintaining acceptable levels of statistical power and experimental validity. While the unbiased deconvolution technique more robustly estimates the shape of the BOLD response functions, both methods succeed in accurately re-producing known differences between evoked BOLD responses when the stimulus ordering is randomized. However, the deconvolution method is more effective at preserving differences when there are sequential dependencies in the stimulus presentation order and restricted ISI distributions are used; particularly if the second of two sequentially dependent stimuli is omitted on some portion of the trials. Importantly, the successful re-production of the evoked BOLD response using restricted ISI distributions often maximizes the ability to make psychologically valid experimental conclusions.
血氧水平依赖（BOLD）反应的形状和持续时间信息可用于功能神经解剖学和心理学理论研究。然而，BOLD反应持续20秒或更长时间，这使得区分时间上相邻刺激所诱发反应的独特特征变得困难。幸运的是，只要刺激间隔（ISI）分布有足够的差异，就可以提取与事件相关的BOLD信号。不幸的是，从心理学角度来看，产生最高统计效率的ISI分布并不总是最优的；刺激时间的变化可能会使根据潜在认知操作对神经成像数据的解释变得复杂。在本文中，使用蒙特卡罗模拟来评估两种估计与事件相关的BOLD时间序列的技术——事件相关平均法和使用普通最小二乘法估计的去卷积法——在保持可接受的统计功效和实验有效性水平方面的表现。虽然无偏去卷积技术能更稳健地估计BOLD反应函数的形状，但当刺激顺序随机化时，两种方法都能成功准确地重现诱发BOLD反应之间的已知差异。然而，当刺激呈现顺序存在序列依赖性且使用受限的ISI分布时，去卷积方法在保留差异方面更有效；特别是如果在某些试验中省略了两个序列相关刺激中的第二个刺激。重要的是，使用受限ISI分布成功重现诱发的BOLD反应通常能最大限度地提高得出具有心理学有效性的实验结论的能力。
