The survivor interaction contrasts (SIC) is a powerful measure for distinguishing among candidate models of human information processing. One class of models to which SIC analysis can apply are the coactive, or channel summation, models of human information processing. In general, parametric forms of coactive models assume that responses are made based on the first passage time across a fixed threshold of a sum of stochastic processes. Previous work has shown that that the SIC for a coactive model based on the sum of Poisson processes has a distinctive down-up-down form, with an early negative region that is smaller than the later positive region. In this note, we demonstrate that a coactive process based on the sum of two Wiener processes has the same SIC form.

中文翻译：

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将 SIC 预测扩展到 Wiener coactive 模型

幸存者交互对比（SIC）是区分人类信息处理候选模型的有力措施。SIC 分析可以应用的一类模型是人类信息处理的协同或通道总和模型。通常，协同模型的参数形式假设响应是基于跨随机过程总和的固定阈值的第一次通过时间做出的。先前的工作表明，基于泊松过程总和的协同模型的 SIC 具有独特的上下形式，早期的负区域小于后来的正区域。在本说明中，我们证明了基于两个维纳过程之和的协同过程具有相同的 SIC 形式。