The critical role of locomotion mechanics in decoding sensory systems
The critical role of locomotion mechanics in decoding sensory systems
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DOI：
10.1523/jneurosci.4198-06.2007
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发表时间：
2007-01-31
影响因子：
5.3
通讯作者：
Fortune, Eric S.
中科院分区：
文献类型：
--
作者：
Cowan, Noah J.;Fortune, Eric S.
神经系统是如何处理感觉信息来控制运动的？弱电刀鱼本征曼尼亚是研究感觉运动控制的理想模型，它游泳是为了稳定正弦运动避难所的感觉图像。当激励频率小于1赫兹时，跟踪性能最佳。运动学分析被广泛应用于运动神经控制的研究中，它相应地预测了控制的低通感觉处理。然而，将牛顿力学纳入对行为的分析，彻底改变了预测：这一分析预测感觉处理是高通的。然而，低通行为由高通神经过滤器控制的这一违反直觉的预测与之前报道的、但在感觉传入和下游神经元中看到的知之甚少的高通过滤相吻合。此外，包含高通控制器的模型与动物行为匹配，而包含低通控制器的模型不匹配且不稳定。由于运动机制在广泛的动物中是相似的，这些数据表明这种高通感官过滤器可能是用于任务级运动控制的一般机制。此外，这些数据突出了除了在神经控制系统研究中广泛使用的运动学分析之外，机械分析的关键作用。
How do neural systems process sensory information to control locomotion? The weakly electric knifefish Eigenmannia, an ideal model for studying sensorimotor control, swims to stabilize the sensory image of a sinusoidally moving refuge. Tracking performance is best at stimulus frequencies less than similar to 1 Hz. Kinematic analysis, which is widely used in the study of neural control of movement, predicts commensurately low-pass sensory processing for control. The inclusion of Newtonian mechanics in the analysis of the behavior, however, categorically shifts the prediction: this analysis predicts that sensory processing is high pass. The counterintuitive prediction that a low-pass behavior is controlled by a high-pass neural filter nevertheless matches previously reported but poorly understood high-pass filtering seen in electrosensory afferents and downstream neurons. Furthermore, a model incorporating the high-pass controller matches animal behavior, whereas the model with the low-pass controller does not and is unstable. Because locomotor mechanics are similar in a wide array of animals, these data suggest that such high-pass sensory filters may be a general mechanism used for task-level locomotion control. Furthermore, these data highlight the critical role of mechanical analyses in addition to widely used kinematic analyses in the study of neural control systems.