A Proposed Circuit Computation in Basal Ganglia: History-Dependent Gain
A Proposed Circuit Computation in Basal Ganglia: History-Dependent Gain
复制标题
DOI：
10.1002/mds.27321
复制
发表时间：
2018-05-01
影响因子：
8.6
通讯作者：
Dudman, Joshua Tate
中科院分区：
文献类型：
--
作者：
Yttri, Eric Allen;Dudman, Joshua Tate
在这篇《科学展望》中，我们首先回顾了我们对基底神经节回路功能结构的理解的最新进展。然后我们认为，这些数据可以用一个模型来最好地解释，在这个模型中，基底节根据先前的经验控制运动运动学的增益，从而形成表现，我们称之为历史相关的增益计算。最后，我们讨论了来自历史依赖的增益模型的见解如何从替补席上转移到床边，主要是对自适应脑深部刺激设计的影响。因此，我们阐述了一个规范的计算模型的关键经验和概念支持，该模型对基底神经节环路在健康和疾病中的广泛作用具有实质性的解释力。(C)2018年作者。《运动障碍》由威利期刊公司代表国际帕金森和运动障碍协会出版。
In this Scientific Perspectives we first review the recent advances in our understanding of the functional architecture of basal ganglia circuits. Then we argue that these data can best be explained by a model in which basal ganglia act to control the gain of movement kinematics to shape performance based on prior experience, which we refer to as a history-dependent gain computation. Finally, we discuss how insights from the history-dependent gain model might translate from the bench to the bedside, primarily the implications for the design of adaptive deep brain stimulation. Thus, we explicate the key empirical and conceptual support for a normative, computational model with substantial explanatory power for the broad role of basal ganglia circuits in health and disease. (c) 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.