Online control of reach accuracy in mice
Online control of reach accuracy in mice
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DOI：
10.1152/jn.00324.2020
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发表时间：
2020-12-01
影响因子：
2.5
通讯作者：
Person, Abigail L.
中科院分区：
文献类型：
--
作者：
Becker, Matthew, I;Calame, Dylan J.;Person, Abigail L.
刘建军，刘建军，刘建军，等。一种基于神经网络的神经网络控制方法。[J] .中国生物医学工程学报，2016,31(4):557 - 557。2020年9月30日首次发布；doi: 10.1152 / jn.00324.2020。-伸展运动作为一种基本而又复杂的运动行为，是神经科学的基础模型系统。特别是，最近对小鼠伸手行为的神经回路机制的研究有了显著的扩展。然而，小鼠肢体运动学的量化仍然缺乏，限制了与灵长类文献的比较。在这项研究中，我们定量地证明了小鼠到达运动学与灵长类动物到达运动学的同源性，并发现了新的后期相关结构，这意味着在线控制。总的来说，我们的研究结果强调了覆盖的减速阶段对于推动成功结果的重要性。具体来说，我们开发并实现了一种新的统计机器学习算法，以识别与成功到达相关的运动学特征，并发现后期运动学最能预测结果，这意味着在线到达控制，而不是预先计划。此外，我们识别并描述了与肢体的飞行位置和速度相关联的后期运动学调整，允许对初始变异性进行动态校正，与自由行为的到达相比，头部固定的到达较少依赖于位置。此外，连续到达显示位置误差纠正，但不热手性，暗示对手调节运动可变性。总的来说，我们的研究结果在神经科学研究的背景下建立了基本的鼠标触手运动学，将鼠标触手的产生描述为一个依赖于动态在线控制机制的主动过程。新的和值得注意的是，老鼠使用伸手动作来抓住和操纵环境中的物体，类似于灵长类动物。为了更好地将小鼠到达作为运动控制的模型，我们实施了几个分析框架，从基本的运动学关系到统计机器学习，来量化小鼠的到达，发现灵长类动物到达的许多典型特征在小鼠中是保守的，以及飞行中段修正的证据，扩大了小鼠到达范式在运动控制研究中的实用性。
Becker MI, Calame DJ, Wrobel J, Person AL. Online control of reach accuracy in mice. J Neurophysiol 124: 1637-1655, 2020. First published September 30, 2020; doi:10.1152/jn.00324.2020.- Reaching movements, as a basic yet complex motor behavior, are a foundational model system in neuroscience. In particular, there has been a significant recent expansion of investigation into the neural circuit mechanisms of reach behavior in mice. Nevertheless, quantification of mouse reach kinematics remains lacking, limiting comparison to the primate literature. In this study, we quantitatively demonstrate the homology of mouse reach kinematics to primate reach and also discover novel late-phase correlational structure that implies online control. Overall, our results highlight the decelerative phase of reach as important in driving successful outcome. Specifically, we develop and implement a novel statistical machine-learning algorithm to identify kinematic features associated with successful reaches and find that late-phase kinematics are most predictive of outcome, signifying online reach control as opposed to preplanning. Moreover, we identify and characterize late-phase kinematic adjustments that are yoked to midflight position and velocity of the limb, allowing for dynamic correction of initial variability, with head-fixed reaches being less dependent on position in comparison to freely behaving reaches. Furthermore, consecutive reaches exhibit positional error correction but not hot-handedness, implying opponent regulation of motor variability. Overall, our results establish foundational mouse reach kinematics in the context of neuroscientific investigation, characterizing mouse reach production as an active process that relies on dynamic online control mechanisms.NEW & NOTEWORTHY Mice use reaching movements to grasp and manipulate objects in their environment, similar to primates. To better establish mouse reach as a model for motor control, we implement several analytical frameworks, from basic kinematic relationships to statistical machine learning, to quantify mouse reach, finding many canonical features of primate reaches are conserved in mice, as well as evidence for midflight course corrections, expanding the utility of mouse reach paradigms for motor control studies.