A rapid whisker-based decision underlying skilled locomotion in mice.
A rapid whisker-based decision underlying skilled locomotion in mice.
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DOI：
10.7554/elife.63596
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发表时间：
2021-01-11
期刊：
影响因子：
7.7
通讯作者：
Sawtell NB
中科院分区：
文献类型：
--
作者：
Warren RA;Zhang Q;Hoffman JR;Li EY;Hong YK;Bruno RM;Sawtell NB
熟练的运动行为需要快速整合外部感官输入和内部状态信息，以决定下一步的动作。利用机器学习方法进行高分辨率运动学分析，我们揭示了小鼠感官引导运动背后的快速决策逻辑。在用胡须探测到障碍物后，小鼠根据胡须对障碍物位置的估计以及它们身体的位置和速度，选择不同的运动策略。虽然小鼠依靠胡须来躲避障碍物，但初级胡须感觉皮层的损伤影响很小。虽然运动皮层的操作影响了所选策略的执行，但决策过程在很大程度上保持不变。这些结果突出了机器学习在自然行为的还原论分析中的潜力，并提供了一个皮层下大脑结构足以介导相对复杂的感觉运动决策的案例。
Skilled motor behavior requires rapidly integrating external sensory input with information about internal state to decide which movements to make next. Using machine learning approaches for high-resolution kinematic analysis, we uncover the logic of a rapid decision underlying sensory-guided locomotion in mice. After detecting obstacles with their whiskers mice select distinct kinematic strategies depending on a whisker-derived estimate of obstacle location together with the position and velocity of their body. Although mice rely on whiskers for obstacle avoidance, lesions of primary whisker sensory cortex had minimal impact. While motor cortex manipulations affected the execution of the chosen strategy, the decision-making process remained largely intact. These results highlight the potential of machine learning for reductionist analysis of naturalistic behaviors and provide a case in which subcortical brain structures appear sufficient for mediating a relatively sophisticated sensorimotor decision.