Suppr超能文献

你的手臂在哪里?本体感知在空间和任务中的变化。

Where is your arm? Variations in proprioception across space and tasks.

机构信息

Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA.

出版信息

J Neurophysiol. 2010 Jan;103(1):164-71. doi: 10.1152/jn.00494.2009. Epub 2009 Oct 28.

Abstract

The sense of limb position is crucial for movement control and environmental interactions. Our understanding of this fundamental proprioceptive process, however, is limited. For example, little is known about the accuracy of arm proprioception: Does it vary with changes in arm configuration, since some peripheral receptors are engaged only when joints move toward extreme angles? Are these variations consistent across different tasks? Does proprioceptive ability change depending on what we try to localize (e.g., fingertip position vs. elbow angle)? We used a robot exoskeleton to study proprioception in 14 arm configurations across three tasks, asking healthy subjects to 1) match a pointer to elbow angles after passive movements, 2) match a pointer to fingertip positions after passive movements, and 3) actively match their elbow angle to a pointer. Across all three tasks, subjects overestimated more extreme joint positions; this may be due to peripheral sensory signals biasing estimates as a safety mechanism to prevent injury. We also found that elbow angle estimates were more precise when used to judge fingertip position versus directly reported, suggesting that the brain has better access to limb endpoint position than joint angles. Finally, precision of elbow angle estimates improved in active versus passive movements, corroborating work showing that efference copies of motor commands and alpha-gamma motor neuron coactivation contribute to proprioceptive estimates. In sum, we have uncovered fundamental aspects of normal proprioceptive processing, demonstrating not only predictable biases that are dependent on joint configuration and independent of task but also improved precision when integrating information across joints.

摘要

肢体位置感对于运动控制和环境交互至关重要。然而,我们对这一基本本体感受过程的理解还很有限。例如,我们对手臂本体感觉的准确性知之甚少:由于只有当关节移动到极端角度时,一些外周感受器才会被激活,那么手臂构型的变化是否会影响它的准确性?这些变化在不同任务中是否一致?本体感觉能力是否会因我们试图定位的内容(例如指尖位置与肘部角度)而改变?我们使用机器人外骨骼在三个任务中研究了 14 种手臂构型的本体感觉,要求健康受试者 1)在被动运动后将指针与肘部角度匹配,2)在被动运动后将指针与指尖位置匹配,3)主动将肘部角度与指针匹配。在所有三个任务中,受试者都高估了更极端的关节位置;这可能是由于外周感觉信号会产生偏差,作为一种安全机制来防止受伤。我们还发现,当用于判断指尖位置时,肘部角度的估计比直接报告更精确,这表明大脑对肢体末端位置的访问比关节角度更好。最后,主动运动与被动运动相比,肘部角度估计的精度提高了,这与证明运动指令的传出副本和α-γ运动神经元共同激活有助于本体感觉估计的工作一致。总之,我们揭示了正常本体感觉处理的基本方面,不仅证明了依赖于关节构型且与任务无关的可预测偏差,而且还证明了在整合关节信息时精度的提高。

相似文献

3
The cerebellum contributes to proprioception during motion.小脑在运动过程中有助于本体感觉。
J Neurophysiol. 2017 Aug 1;118(2):693-702. doi: 10.1152/jn.00417.2016. Epub 2017 Apr 12.
5
Sensorimotor adaptation in response to proprioceptive bias.响应本体感觉偏差的感觉运动适应。
Exp Brain Res. 2007 Feb;177(2):147-56. doi: 10.1007/s00221-006-0658-5. Epub 2006 Sep 7.
10
Influence of fingertip contact on illusory arm movements.指尖接触对虚幻手臂运动的影响。
J Appl Physiol (1985). 2004 Apr;96(4):1555-60. doi: 10.1152/japplphysiol.01085.2003. Epub 2003 Dec 29.

引用本文的文献

5
Neural correlates of bilateral proprioception and adaptation with training.双侧本体感受和适应训练的神经相关性。
PLoS One. 2024 Mar 15;19(3):e0299873. doi: 10.1371/journal.pone.0299873. eCollection 2024.
6
Expanding the framework of proprioception: a comment on Héroux et al.拓展本体感觉的框架:对赫鲁克斯等人的评论
J Appl Physiol (1985). 2024 Mar 1;136(3):509-510. doi: 10.1152/japplphysiol.00880.2023.
9
Proprioceptive disturbances in weightlessness revisited.失重状态下本体感觉障碍再探讨。
NPJ Microgravity. 2023 Aug 11;9(1):64. doi: 10.1038/s41526-023-00318-8.

本文引用的文献

5
Motor commands contribute to human position sense.运动指令有助于人体的位置感知。
J Physiol. 2006 Mar 15;571(Pt 3):703-10. doi: 10.1113/jphysiol.2005.103093. Epub 2006 Jan 26.
9
Proprioceptive population coding of limb position in humans.人类肢体位置的本体感觉群体编码。
Exp Brain Res. 2003 Apr;149(4):512-9. doi: 10.1007/s00221-003-1384-x. Epub 2003 Feb 7.

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验