信息流通过C. elegans趋旋回路
Information flow through a model of the C. elegans klinotaxis circuit
摘要：
了解外界刺激的信息如何转化为行为是神经科学的核心目标之一。在这里，我们描述了通过一个完整的感觉运动回路的信息流：从刺激，感觉神经元，中间神经元，运动神经元，肌肉，运动。具体来说，我们应用最近开发的框架，用于量化信息流到以前发表的合奏模型盐klinotaxis线虫C。优雅这些模型以神经解剖学和目前已知的蠕虫神经生理学为基础。对未知的模型参数进行了优化，以再现蠕虫的行为。信息流分析揭示了模型运作的几个关键原则：（1）中间神经元类AIY负责整合关于浓度正变化和负变化的信息，并表现出强烈的左/右信息不对称。(2)间隙连接在负责在中间神经元类AIZ中观察到的信息对称性的信息传递中起着至关重要的作用。(3)颈部运动神经元类SMB实现了一种信息门控机制，该机制是电路的状态依赖性响应的基础。(4)颈部携带浓度变化的非均匀分布。因此，并非所有的运动方向都具有同样的信息量。这些发现中的每一个都对应于一个实验预测，可以在蠕虫中进行测试，以大大改善我们对趋动性背后的神经回路的理解。信息流分析还使我们能够探索信息流如何与潜在的电生理学相关。尽管个体电路的神经参数变化很大，但整个信息流架构电路在整个集合中是非常一致的，这表明信息流分析捕获了趋动性电路的一般操作原理。
英文摘要：
Understanding how information about external stimuli is transformed into behavior is one of the central goals of neuroscience. Here we characterize the information flow through a complete sensorimotor circuit: from stimulus, to sensory neurons, to interneurons, to motor neurons, to muscles, to motion. Specifically, we apply a recently developed framework for quantifying information flow to a previously published ensemble of models of salt klinotaxis in the nematode worm C. elegans. The models are grounded in the neuroanatomy and currently known neurophysiology of the worm. The unknown model parameters were optimized to reproduce the worm's behavior. Information flow analysis reveals several key principles underlying how the models operate: (1) Interneuron class AIY is responsible for integrating information about positive and negative changes in concentration, and exhibits a strong left/right information asymmetry. (2) Gap junctions play a crucial role in the transfer of information responsible for the information symmetry observed in interneuron class AIZ. (3) Neck motor neuron class SMB implements an information gating mechanism that underlies the circuit's state-dependent response. (4) The neck carries non-uniform distribution about changes in concentration. Thus, not all directions of movement are equally informative. Each of these findings corresponds to an experimental prediction that could be tested in the worm to greatly refine our understanding of the neural circuit underlying klinotaxis. Information flow analysis also allows us to explore how information flow relates to underlying electrophysiology. Despite large variations in the neural parameters of individual circuits, the overall information flow architecture circuit is remarkably consistent across the ensemble, suggesting that information flow analysis captures general principles of operation for the klinotaxis circuit.
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