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不精确预测编码是经典精神分裂症的核心。

Imprecise Predictive Coding Is at the Core of Classical Schizophrenia.

作者信息

Liddle Peter F, Liddle Elizabeth B

机构信息

Centre for Translational Neuroimaging for Mental Health, School of Medicine, Institute of Mental Health, University of Nottingham, Nottingham, United Kingdom.

出版信息

Front Hum Neurosci. 2022 Mar 3;16:818711. doi: 10.3389/fnhum.2022.818711. eCollection 2022.

Abstract

Current diagnostic criteria for schizophrenia place emphasis on delusions and hallucinations, whereas the classical descriptions of schizophrenia by Kraepelin and Bleuler emphasized disorganization and impoverishment of mental activity. Despite the availability of antipsychotic medication for treating delusions and hallucinations, many patients continue to experience persisting disability. Improving treatment requires a better understanding of the processes leading to persisting disability. We recently introduced the term classical schizophrenia to describe cases with disorganized and impoverished mental activity, cognitive impairment and predisposition to persisting disability. Recent evidence reveals that a polygenic score indicating risk for schizophrenia predicts severity of the features of classical schizophrenia: disorganization, and to a lesser extent, impoverishment of mental activity and cognitive impairment. Current understanding of brain function attributes a cardinal role to predictive coding: the process of generating models of the world that are successively updated in light of confirmation or contradiction by subsequent sensory information. It has been proposed that abnormalities of these predictive processes account for delusions and hallucinations. Here we examine the evidence provided by electrophysiology and fMRI indicating that imprecise predictive coding is the core pathological process in classical schizophrenia, accounting for disorganization, psychomotor poverty and cognitive impairment. Functional imaging reveals aberrant brain activity at network hubs engaged during encoding of predictions. We discuss the possibility that frequent prediction errors might promote excess release of the neurotransmitter, dopamine, thereby accounting for the occurrence of episodes of florid psychotic symptoms including delusions and hallucinations in classical schizophrenia. While the predictive coding hypotheses partially accounts for the time-course of classical schizophrenia, the overall body of evidence indicates that environmental factors also contribute. We discuss the evidence that chronic inflammation is a mechanism that might link diverse genetic and environmental etiological factors, and contribute to the proposed imprecision of predictive coding.

摘要

精神分裂症的当前诊断标准侧重于妄想和幻觉,而克雷佩林和布鲁勒对精神分裂症的经典描述则强调精神活动的紊乱和匮乏。尽管有抗精神病药物可用于治疗妄想和幻觉,但许多患者仍持续存在残疾状况。改善治疗需要更好地理解导致持续残疾的过程。我们最近引入了“经典精神分裂症”这一术语,以描述具有精神活动紊乱、匮乏、认知障碍以及持续残疾倾向的病例。最近的证据表明,一个表明精神分裂症风险的多基因评分可预测经典精神分裂症特征的严重程度:即紊乱,以及在较小程度上的精神活动匮乏和认知障碍。目前对脑功能的理解将关键作用归因于预测编码:即根据后续感官信息的证实或矛盾来不断更新世界模型的过程。有人提出,这些预测过程的异常可解释妄想和幻觉。在此,我们研究了电生理学和功能磁共振成像提供的证据,这些证据表明不精确的预测编码是经典精神分裂症的核心病理过程,可解释紊乱、精神运动性匮乏和认知障碍。功能成像显示在预测编码过程中参与的网络枢纽存在异常脑活动。我们讨论了频繁的预测误差可能促进神经递质多巴胺过度释放的可能性,从而解释了经典精神分裂症中包括妄想和幻觉在内的明显精神病症状发作的发生。虽然预测编码假说部分解释了经典精神分裂症的病程,但总体证据表明环境因素也有作用。我们讨论了慢性炎症是一种可能将多种遗传和环境病因因素联系起来并导致所提出的预测编码不精确的机制的证据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/16bf/8928728/7969cc983566/fnhum-16-818711-g001.jpg

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