A multivariate, multitaper approach to detecting and estimating harmonic response in cortical optical imaging data.
A multivariate, multitaper approach to detecting and estimating harmonic response in cortical optical imaging data.
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DOI：
10.1016/j.jneumeth.2011.09.018
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发表时间：
2012-01-15
影响因子：
3
通讯作者：
Yokoo, T.
中科院分区：
文献类型：
--
作者：
Sornborger, A. T.;Yokoo, T.
关键词：
使用周期性刺激方案提高了光学成像实验的皮质图的效率和准确性。由此产生的数据分析需要检测和估计多元数据集中的周期性信息。迄今为止，这些分析依赖于离散傅里叶变换 (DFT) 正弦曲线估计。多锥度方法已成为单变量时间序列分析中的常用统计工具，可以提供改进的估计。在这里，我们将单变量多锥谐波分析方法扩展到多元成像环境。假设指定带宽内存在跨多个像素的相干振荡，我们通过构建 Hotelling 的广义 T2 检验来研究其在噪声数据中的检测和估计问题。然后，我们在两个上下文中扩展对该问题的研究，即标准典型变量分析（CVA）和广义指示函数分析（GIFA），后者在提取空间相关噪声中的信号时通常更稳健。我们提供了有关使用我们的方法发现的平均估计保真度以及与 DFT 估计的比较的详细信息。我们的结果表明，GIFA 对空间相关噪声中的谐波信号提供了特别好的估计，并且对于检测空间相关噪声常见的生物成像测量等应用中的小幅度谐波信号非常有用。我们通过猫视觉皮层中周期性旋转定向漂移光栅刺激实验的周期性响应的光学成像数据集展示了我们方法的强大功能。
The efficiency and accuracy of cortical maps from optical imaging experiments have been improved using periodic stimulation protocols. The resulting data analysis requires the detection and estimation of periodic information in a multivariate dataset. To date, these analyses have relied on discrete Fourier transform (DFT) sinusoid estimates. Multitaper methods have become common statistical tools in the analysis of univariate time series that can give improved estimates. Here, we extend univariate multitaper harmonic analysis methods to the multivariate, imaging context. Given the hypothesis that a coherent oscillation across many pixels exists within a specified bandwidth, we investigate the problem of its detection and estimation in noisy data by constructing Hotelling’s generalized T2-test. We then extend the investigation of this problem in two contexts, that of standard Canonical Variate Analysis (CVA) and that of Generalized Indicator Function Analysis (GIFA) which is often more robust in extracting a signal in spatially correlated noise. We provide detailed information on the fidelities of the mean estimates found with our methods and comparison with DFT estimates. Our results indicate that GIFA provides particularly good estimates of harmonic signals in spatially correlated noise and is useful for detecting small amplitude harmonic signals in applications such as biological imaging measurements where spatially correlated noise is common. We demonstrate the power of our methods with an optical imaging dataset of the periodic response to a periodically rotating oriented drifting grating stimulus experiment in cat visual cortex.
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影响因子：
5.3
作者：
BLASDEL, GG
通讯作者：
BLASDEL, GG
影响因子：
3.4
作者：
Mitra, PP;Pesaran, B
通讯作者：
Pesaran, B
DOI：
10.1073/pnas.0505592102
发表时间：
2005-09-13
影响因子：
11.1
作者：
Kalatsky, VA;Polley, DB;Stryker, MP
通讯作者：
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DOI：
10.1073/pnas.95.14.8334
发表时间：
1998-07-07
影响因子：
11.1
作者：
Everson, RM;Prashanth, AK;Kaplan, E
通讯作者：
Kaplan, E
影响因子：
3
作者：
Somborger, A;Yokoo, T;Sirovich, L
通讯作者：
Sirovich, L