Department of Statistics and Operations Research, University of Vigo, Vigo, Pontevedra, Spain.
Stat Med. 2011 Jun 30;30(14):1695-711. doi: 10.1002/sim.4220. Epub 2011 Mar 24.
It is well established that neural activity is stochastically modulated over time. Therefore, direct comparisons across experimental conditions and determination of change points or maximum firing rates are not straightforward. This study sought to compare temporal firing probability curves that may vary across groups defined by different experimental conditions. Odds-ratio (OR) curves were used as a measure of comparison, and the main goal was to provide a global test to detect significant differences of such curves through the study of their derivatives. An algorithm is proposed that enables ORs based on generalized additive models, including factor-by-curve-type interactions to be flexibly estimated. Bootstrap methods were used to draw inferences from the derivatives curves, and binning techniques were applied to speed up computation in the estimation and testing processes. A simulation study was conducted to assess the validity of these bootstrap-based tests. This methodology was applied to study premotor ventral cortex neural activity associated with decision-making. The proposed statistical procedures proved very useful in revealing the neural activity correlates of decision-making in a visual discrimination task.
已有研究证实，神经活动随时间呈随机调制。因此，在不同的实验条件下直接进行比较，或者确定变化点或最大发放率并不简单。本研究旨在比较可能因不同实验条件而在组间变化的时间发放概率曲线。优势比（OR）曲线被用作比较的度量标准，主要目的是通过研究其导数来提供一种全局测试，以检测此类曲线的显著差异。提出了一种算法，能够灵活地估计基于广义加性模型的 OR，包括因子与曲线类型的交互作用。使用自举方法从导数曲线中进行推断，并应用分箱技术来加速估计和测试过程中的计算。进行了一项模拟研究来评估这些基于自举的测试的有效性。该方法应用于研究与决策相关的运动前腹侧皮层的神经活动。所提出的统计程序在揭示视觉辨别任务中决策的神经活动相关性方面非常有用。
