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Beyond Autism: Introducing the Dialectical Misattunement Hypothesis and a Bayesian Account of Intersubjectivity

机译:除了自闭症之外:介绍辩证的检测假设和贝叶斯的差距性

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Drawing on sociocultural theories and Bayesian accounts of brain function, in this article we construe psychiatric conditions as disorders of social interaction to fully account for their complexity and dynamicity across levels of description and temporal scales. After an introduction of the theoretical underpinnings of our integrative approach, we take autism spectrum conditions (ASC) as a paradigm example and discuss how neurocognitive hypotheses can be translated into a Bayesian formulation, i.e., in terms of predictive processing and active inference. We then argue that consideration of individuals (even within a Bayesian framework) will not be enough for a comprehensive understanding of psychiatric conditions and consequently put forward the dialectical misattunement hypothesis, which views psychopathology not merely as disordered function within single brains but also as a dynamic interpersonal mismatch that encompasses various levels of description. Moving from a mere comparison of groups, i.e., "healthy" persons versus "patients," to a fine-grained analysis of social interactions within dyads and groups of individuals will open new avenues and may allow to avoid an overly neurocentric scope in psychiatric research as well as help to reduce social exclusion. (C) 2017 S. Karger AG, Basel
机译:绘制社会文化理论和贝叶斯脑功能衰退,在本文中,我们将精神病条件视为社会互动的障碍,以完全占他们跨描述和时间尺度水平的复杂性和动力学。在引入我们的综合方法的理论支撑之后,我们将自闭症频谱条件(ASC)作为范例示例,并讨论了神经认知假设如何转化为贝叶斯配方,即,就预测处理和有效推断而言。然后,我们争辩说,对个人的思考(即使在贝叶斯框架内)对精神病条件的全面了解,并因此提出了辩证检测假设,这意见不仅仅是单一大脑内的函数,而且是一种动态涵盖各种描述的人际关系不匹配。从仅仅比较群体的比较,即“健康”人类对“患者”,对Dyads和个人群体中的社会互动进行细粒度分析,将开辟新的途径,并可能避免在精神病学研究中避免过度神经中心的范围以及帮助减少社会排斥。 (c)2017年S. Karger AG,巴塞尔

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