In psychiatry we often speak of constructing “models.” Here we try to make sense of what such a claim might mean, starting with the most fundamental question: “What is (and isn’t) a model?” We then discuss, in a concrete measurable sense, what it means for a model to be useful. In so doing, we first identify the added value that a computational model can provide in the context of accuracy and power. We then present limitations of standard statistical methods and provide suggestions for how we can expand the explanatory power of our analyses by reconceptualizing statistical models as dynamical systems. Finally, we address the problem of model building—suggesting ways in which computational psychiatry can escape the potential for cognitive biases imposed by classical hypothesis-driven research, exploiting deep systems-level information contained within neuroimaging data to advance our understanding of psychiatric neuroscience.

中文翻译：

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理解计算精神病学。

在精神病学中，我们经常谈到构建“模型”。在这里，我们试图理解这种说法可能意味着什么，从最基本的问题开始：“什么是（和不是）模型？” 然后，我们在具体可衡量的意义上讨论模型的有用性意味着什么。在这样做时，我们首先确定计算模型在准确性和功率方面可以提供的附加值。然后，我们提出了标准统计方法的局限性，并就如何通过将统计模型重新定义为动态系统来扩展分析的解释力提供建议。最后，我们解决了模型构建的问题——建议计算精神病学可以避免经典假设驱动研究强加的潜在认知偏差的方法，