Exploring effective multiplicity in multichannel functional near-infrared spectroscopy using eigenvalues of correlation matrices.
Exploring effective multiplicity in multichannel functional near-infrared spectroscopy using eigenvalues of correlation matrices.
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使用相关矩阵的特征值探索多通道功能近红外光谱中的有效多重性。
DOI：
10.1117/1.nph.2.1.015002
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发表时间：
2015
期刊：
影响因子：
5.3
通讯作者：
Eiju Watanabe
中科院分区：
文献类型：
--
作者：
Minako Uga;Ippeita Dan;Haruka Dan;Yasushi Kyutoku;Y-h Taguchi;Eiju Watanabe
多通道功能近红外光谱（fNIRS）的最新进展允许广泛覆盖的皮层区域，同时需要控制家庭明智的错误（FWE），由于增加的多样性。通常，Bonferroni方法已被用于控制FWE。虽然可以严格控制I类错误（误报），但应用大量通道设置可能会增加II类错误（漏报）的机会。基于Bonferroni的方法在控制具有最小值的最活跃通道的I型错误方面特别严格。为了保持I型和II型错误之间的平衡，从相关矩阵的特征值导出的有效多重性（）是遗传学研究中引入的一种方法。因此，我们探讨了其在多通道fNIRS研究中的可行性。将该方法应用于三种不同激活曲线的实验数据，我们进行了响应模拟，发现在44通道设置中，响应控制在10到15。因此，显著激活的通道的数量几乎保持恒定，而不管测量的通道的数量。我们证明，该方法可以有效地替代Bonferroni为基础的方法进行多通道fNIRS研究。
Recent advances in multichannel functional near-infrared spectroscopy (fNIRS) allow wide coverage of cortical areas while entailing the necessity to control family-wise errors (FWEs) due to increased multiplicity. Conventionally, the Bonferroni method has been used to control FWE. While Type I errors (false positives) can be strictly controlled, the application of a large number of channel settings may inflate the chance of Type II errors (false negatives). The Bonferroni-based methods are especially stringent in controlling Type I errors of the most activated channel with the smallestvalue. To maintain a balance between Types I and II errors, effective multiplicity () derived from the eigenvalues of correlation matrices is a method that has been introduced in genetic studies. Thus, we explored its feasibility in multichannel fNIRS studies. Applying themethod to three kinds of experimental data with different activation profiles, we performed resampling simulations and found thatwas controlled at 10 to 15 in a 44-channel setting. Consequently, the number of significantly activated channels remained almost constant regardless of the number of measured channels. We demonstrated that theapproach can be an effective alternative to Bonferroni-based methods for multichannel fNIRS studies.