A key assumption of models of human cognition is that there is variability in information processing. Evidence accumulation models (EAMs) commonly assume 2 broad variabilities in information processing: within-trial variability, which is thought to reflect moment-to-moment fluctuations in perceptual processes, and between-trial variability, which is thought to reflect variability in slower-changing processes like attention, or systematic variability between the stimuli on different trials. Recently, Ratcliff, Voskuilen, and McKoon (2018) claimed to "provide direct evidence that external noise is, in fact, required to explain the data from five simple two-choice decision tasks" (p. 33), suggesting that at least some portion of the between-trial variability in information processing is due to "noise." However, we argue that Ratcliff et al. (2018) failed to distinguish between 2 different potential sources of between-trial variability: random (i.e., "external noise") and systematic (e.g., item effects). Contrary to the claims of Ratcliff et al. (2018), we show that "external noise" is not required to explain their findings, as the same trends of data can be produced when only item effects are present. Furthermore, we contend that the concept of "noise" within cognitive models merely serves as a convenience parameter for sources of variability that we know exist but are unable to account for. Therefore, we question the usefulness of experiments aimed at testing the general existence of "random" variability and instead suggest that future research should attempt to replace the random variability terms within cognitive models with actual explanations of the process. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

中文翻译：

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感知决策中系统性和随机性的可变性来源：对Ratcliff，Voskuilen和McKoon（2018）的评论。

人类认知模型的关键假设是信息处理中存在可变性。证据累积模型（EAM）通常假定信息处理中有2种广泛的变化：审判内的变化（被认为反映了感知过程中的瞬间到瞬间的波动）和审判之间的变化（被认为反映了慢速过程中的变化）。改变注意力等过程，或不同试验中刺激之间的系统差异。最近，Ratcliff，Voskuilen和McKoon（2018）声称“提供了直接证据，证明实际上需要外部噪声来解释来自五个简单的两选决策任务的数据”（第33页），这表明至少有一些信息处理中两次试用之间的可变性的一部分是由于“噪声”造成的。然而，我们认为Ratcliff等人。（2018）未能区分试验间变异的两个不同潜在来源：随机（即“外部噪声”）和系统性（例如项目效应）。与Ratcliff等人的主张相反。（2018），我们证明不需要“外部噪音”来解释他们的发现，因为当仅存在项目效应时，可以产生相同的数据趋势。此外，我们认为认知模型中“噪声”的概念仅作为便利变量，用于我们知道存在但无法解释的可变性来源。因此，我们质疑旨在测试“随机”的普遍存在的实验的有用性 可变性，并建议未来的研究应尝试用对过程的实际解释来替换认知模型中的随机可变性项。（PsycInfo数据库记录（c）2020 APA，保留所有权利）。