Liou Michelle, Su Hong-Ren, Lee Juin-Der, Aston John A D, Tsai Arthur C, Cheng Philip E
Institute of Statistical Science, Academia Sinica, Taipei 115, Taiwan.
Neuroimage. 2006 Jan 15;29(2):383-95. doi: 10.1016/j.neuroimage.2005.08.015. Epub 2005 Oct 14.
Insights into cognitive neuroscience from neuroimaging techniques are now required to go beyond the localisation of well-known cognitive functions. Fundamental to this is the notion of reproducibility of experimental outcomes. This paper addresses the central issue that functional magnetic resonance imaging (fMRI) experiments will produce more desirable information if researchers begin to search for reproducible evidence rather than only p value significance. The study proposes a methodology for investigating reproducible evidence without conducting separate fMRI experiments. The reproducible evidence is gathered from the separate runs within the study. The associated empirical Bayes and ROC extensions of the linear model provide parameter estimates to determine reproducibility. Empirical applications of the methodology suggest that reproducible evidence is robust to small sample sizes and sensitive to both the magnitude and persistency of brain activation. It is demonstrated that research findings in fMRI studies would be more compelling with supporting reproducible evidence in addition to standard hypothesis testing evidence.
现在需要从神经成像技术中获得对认知神经科学的见解，以超越对著名认知功能的定位。这其中的根本是实验结果的可重复性概念。本文探讨了一个核心问题，即如果研究人员开始寻找可重复的证据，而不仅仅是p值显著性，功能磁共振成像（fMRI）实验将产生更理想的信息。该研究提出了一种无需进行单独的fMRI实验来调查可重复证据的方法。可重复证据是从研究中的单独运行中收集的。线性模型的相关经验贝叶斯和ROC扩展提供参数估计以确定可重复性。该方法的实证应用表明，可重复证据对小样本量具有鲁棒性，并且对大脑激活的幅度和持续性都很敏感。结果表明，除了标准的假设检验证据外，fMRI研究中的研究结果若有支持性的可重复证据将更具说服力。
