Temporal processing and context dependency in C. elegans mechanosensation dataset

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. Here we present over 8,000 animal hours of behavior recordings to investigate the nematode C. elegans' response to time-varying mechanosensory signals. We use a high-throughput optogenetic assay, video microscopy 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, a statistical analysis of these recordings find that the nervous system is tuned to temporal properties of mechanosensory signals, like its integral and derivative, that extend over many seconds. We show that 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. We present these findings, and a linear-nonlinear model that predicts the animal's behavioral response to stimulus, in an accompanying manuscript, Liu et al., “Temporal processing and context dependency in C. elegans mechanosensation” available at https://arxiv.org/abs/1803.04085.

对感官信号如何转化为运动输出的量化理解，对大脑功能施加了有益的约束，并有助于揭示大脑的潜在计算机制。本研究呈现了超过8000小时的动物行为记录，旨在探究秀丽隐杆线虫（C. elegans）对时变机械性感觉信号的响应。我们采用高通量光遗传学检测、视频显微镜及自动行为量化技术。在关于触觉电路的现行模式中，动物的行为由受刺激的神经元及其刺激幅度所决定。然而，对这些记录的统计分析发现，神经系统对机械性感觉信号的时序特性进行了调谐，如其积分和导数，这些特性可跨越数秒。我们揭示了机械性感觉信号，即使在同一神经元中，也可以被定制以引发不同的行为反应。此外，我们发现动物的反应还取决于其行为背景。最为显著的是，在转弯时，动物会忽略所有测试的机械性感觉刺激。我们将在随附的论文中介绍这些发现，以及一个预测动物对刺激行为反应的线性-非线性模型，该论文由刘等著，题为《秀丽隐杆线虫机械感觉中的时间处理和情境依赖性》，可在https://arxiv.org/abs/1803.04085上查阅。