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The neural and neurocomputational bases of recovery from post-stroke aphasia.
Nature Reviews Neurology ( IF 38.1 ) Pub Date : 2019-11-26 , DOI: 10.1038/s41582-019-0282-1
James D Stefaniak 1, 2 , Ajay D Halai 2 , Matthew A Lambon Ralph 2
Affiliation  

Language impairment, or aphasia, is a disabling symptom that affects at least one third of individuals after stroke. Some affected individuals will spontaneously recover partial language function. However, despite a growing number of investigations, our understanding of how and why this recovery occurs is very limited. This Review proposes that existing hypotheses about language recovery after stroke can be conceptualized as specific examples of two fundamental principles. The first principle, degeneracy, dictates that different neural networks are able to adapt to perform similar cognitive functions, which would enable the brain to compensate for damage to any individual network. The second principle, variable neuro-displacement, dictates that there is spare capacity within or between neural networks, which, to save energy, is not used under standard levels of performance demand, but can be engaged under certain situations. These two principles are not mutually exclusive and might involve neural networks in both hemispheres. Most existing hypotheses are descriptive and lack a clear mechanistic account or concrete experimental evidence. Therefore, a better neurocomputational, mechanistic understanding of language recovery is required to inform research into new therapeutic interventions.

中文翻译:

中风后失语症恢复的神经和神经计算基础。

语言障碍或失语症是一种致残症状,在中风后影响至少三分之一的人。一些受影响的个体会自发恢复部分语言功能。然而,尽管进行了越来越多的调查,但我们对这种恢复如何以及为何发生的理解非常有限。本综述提出,关于中风后语言恢复的现有假设可以概念化为两个基本原则的具体例子。第一个原则,简并性,规定不同的神经网络能够适应执行相似的认知功能,这将使大脑能够补偿对任何单个网络的损害。第二个原则,可变神经位移,指示神经网络内部或神经网络之间存在备用容量,为了节省能量,在标准的性能需求水平下不使用,但可以在某些情况下使用。这两个原则并不相互排斥,可能涉及两个半球的神经网络。大多数现有假设都是描述性的,缺乏明确的机制说明或具体的实验证据。因此,需要对语言恢复有更好的神经计算和机械理解,以便为新的治疗干预研究提供信息。
更新日期:2019-11-27
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