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Neural Algorithms and Circuits for Motor Planning
Annual Review of Neuroscience ( IF 13.9 ) Pub Date : 2022-03-22 , DOI: 10.1146/annurev-neuro-092021-121730
Hidehiko K Inagaki 1 , Susu Chen 2 , Kayvon Daie 2, 3 , Arseny Finkelstein 2, 4 , Lorenzo Fontolan 2 , Sandro Romani 2 , Karel Svoboda 2, 3
Affiliation  

The brain plans and executes volitional movements. The underlying patterns of neural population activity have been explored in the context of movements of the eyes, limbs, tongue, and head in nonhuman primates and rodents. How do networks of neurons produce the slow neural dynamics that prepare specific movements and the fast dynamics that ultimately initiate these movements? Recent work exploits rapid and calibrated perturbations of neural activity to test specific dynamical systems models that are capable of producing the observed neural activity. These joint experimental and computational studies show that cortical dynamics during motor planning reflect fixed points of neural activity (attractors). Subcortical control signals reshape and move attractors over multiple timescales, causing commitment to specific actions and rapid transitions to movement execution. Experiments in rodents are beginning to reveal how these algorithms are implemented at the level of brain-wide neural circuits.

中文翻译:

用于运动规划的神经算法和电路

大脑计划并执行意志运动。人们已经在非人类灵长类动物和啮齿类动物的眼睛、四肢、舌头和头部运动的背景下探索了神经群体活动的基本模式。神经元网络如何产生准备特定运动的慢速神经动力学和最终启动这些运动的快速神经动力学?最近的工作利用神经活动的快速且校准的扰动来测试能够产生观察到的神经活动的特定动力系统模型。这些联合实验和计算研究表明,运动规划过程中的皮质动力学反映了神经活动的固定点(吸引子)。皮层下控制信号在多个时间尺度上重塑和移动吸引子,导致对特定行动的承诺并快速过渡到运动执行。啮齿类动物的实验开始揭示这些算法是如何在全脑神经回路水平上实现的。
更新日期:2022-03-22
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