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痴呆症中异常预测编码的证据和意义。

Evidence and implications of abnormal predictive coding in dementia.

机构信息

Cambridge Centre for Frontotemporal Dementia, Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0SZ, UK.

Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge CB2 7EF, UK.

出版信息

Brain. 2021 Dec 16;144(11):3311-3321. doi: 10.1093/brain/awab254.

Abstract

The diversity of cognitive deficits and neuropathological processes associated with dementias has encouraged divergence in pathophysiological explanations of disease. Here, we review an alternative framework that emphasizes convergent critical features of cognitive pathophysiology. Rather than the loss of 'memory centres' or 'language centres', or singular neurotransmitter systems, cognitive deficits are interpreted in terms of aberrant predictive coding in hierarchical neural networks. This builds on advances in normative accounts of brain function, specifically the Bayesian integration of beliefs and sensory evidence in which hierarchical predictions and prediction errors underlie memory, perception, speech and behaviour. We describe how analogous impairments in predictive coding in parallel neurocognitive systems can generate diverse clinical phenomena, including the characteristics of dementias. The review presents evidence from behavioural and neurophysiological studies of perception, language, memory and decision-making. The reformulation of cognitive deficits in terms of predictive coding has several advantages. It brings diverse clinical phenomena into a common framework; it aligns cognitive and movement disorders; and it makes specific predictions on cognitive physiology that support translational and experimental medicine studies. The insights into complex human cognitive disorders from the predictive coding framework may therefore also inform future therapeutic strategies.

摘要

与痴呆症相关的认知缺陷和神经病理过程的多样性促使人们对疾病的病理生理学解释产生分歧。在这里,我们回顾了一个强调认知病理生理学趋同关键特征的替代框架。认知缺陷不是“记忆中心”或“语言中心”的丧失,也不是单一的神经递质系统的丧失,而是根据分层神经网络中的异常预测编码来解释的。这是基于对大脑功能的规范解释的进展,特别是在信念和感官证据的贝叶斯整合中,分层预测和预测错误是记忆、感知、言语和行为的基础。我们描述了类似的预测编码在平行神经认知系统中的损伤如何产生各种临床现象,包括痴呆症的特征。该综述从感知、语言、记忆和决策的行为和神经生理学研究中提供了证据。用预测编码来重新表述认知缺陷有几个优点。它将各种临床现象纳入一个共同的框架;它将认知障碍和运动障碍联系起来;并对支持转化和实验医学研究的认知生理学做出了具体预测。因此,预测编码框架对复杂的人类认知障碍的深入了解也可能为未来的治疗策略提供信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6df4/8677549/1e5023d06f63/awab254f1.jpg

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