The theme of this special issue of the Journal of Abnormal Psychology is on predictive processing and how it can improve our fundamental understanding of neuropsychiatric disorders. Several articles focus on psychosis and demonstrate how the field of computational psychosis research has evolved and matured in recent years through the application of predictive processing theory. These articles suggest that whereas the computational mechanisms underlying psychosis may be complex, careful empirical and theoretical work-using more sophisticated models-can bridge gaps between previous results that appeared to be at odds while providing more explanatory power. There is a particular focus on processing hierarchies; defining which priors are maladaptive and at what stage of illness they become so; and finding compelling neurobiological correlates of computational processes. These articles provide a blueprint for future empirical work. This work-that is licensed theoretically by predictive processing-may improve our understanding of psychosis and its treatment and open new avenues for biomarker and therapeutic development. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

中文翻译：

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全部长大：精神病，复杂性和进步的计算理论。

这本《异常心理学杂志》的特刊的主题是预测过程及其如何改善我们对神经精神疾病的基本理解。几篇文章关注精神病，并通过应用预测性加工理论证明了近年来计算精神病研究领域的发展和成熟。这些文章表明，尽管精神病的计算机制可能很复杂，但仔细的经验和理论工作（使用更复杂的模型）可以弥合先前似乎不一致的结果之间的差距，同时提供更多的解释力。特别关注处理层次结构。定义哪些先验适应不良，以及它们在什么疾病阶段变得如此；并找到计算过程中令人信服的神经生物学关联。这些文章为将来的经验工作提供了一个蓝图。理论上通过预测性处理获得许可的这项工作可能会改善我们对精神病及其治疗的理解，并为生物标志物和治疗的发展开辟新的途径。（PsycInfo数据库记录（c）2020 APA，保留所有权利）。