C语言中的时态处理和上下文依赖。秀丽线虫机械感觉
Temporal processing and context dependency in C. elegans mechanosensation
摘要：
对感觉信号如何转化为运动输出的定量理解对大脑功能产生了有用的约束，并有助于揭示大脑的底层计算。我们研究了线虫C.使用高通量光遗传学测定和自动行为定量，线虫对时变机械感觉信号作出响应。在触摸电路的流行图片中，动物的行为取决于哪些神经元受到刺激以及刺激幅度。相比之下，我们发现，行为反应是调谐到时间特性的mechanosensory信号，如其积分和导数，延长了许多秒。机械感觉信号，即使在相同的神经元中，也可以被定制以引起不同的行为反应。此外，我们发现动物的反应也取决于其行为背景。最戏剧性的是，动物忽略了所有测试mechanosensory刺激在转身。最后，我们提出了一个线性-非线性模型，预测动物的行为反应的刺激。
英文摘要：
A quantitative understanding of how sensory signals are transformed into motor outputs places useful constraints on brain function and helps reveal the brain's underlying computations. We investigate how the nematode C. elegans responds to time-varying mechanosensory signals using a high-throughput optogenetic assay and automated behavior quantification. In the prevailing picture of the touch circuit, the animal's behavior is determined by which neurons are stimulated and by the stimulus amplitude. In contrast, we find that the behavioral response is tuned to temporal properties of mechanosensory signals, like its integral and derivative, that extend over many seconds. Mechanosensory signals, even in the same neurons, can be tailored to elicit different behavioral responses. Moreover, we find that the animal's response also depends on its behavioral context. Most dramatically, the animal ignores all tested mechanosensory stimuli during turns. Finally, we present a linear-nonlinear model that predicts the animal's behavioral response to stimulus.
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