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时空反馈与网络结构驱动并编码秀丽隐杆线虫的运动。

Spatiotemporal Feedback and Network Structure Drive and Encode Caenorhabditis elegans Locomotion.

作者信息

Kunert James M, Proctor Joshua L, Brunton Steven L, Kutz J Nathan

机构信息

Department of Physics, University of Washington, Seattle, Washington, United States of America.

Institute for Disease Modeling, Bellevue, Washington, United States of America.

出版信息

PLoS Comput Biol. 2017 Jan 11;13(1):e1005303. doi: 10.1371/journal.pcbi.1005303. eCollection 2017 Jan.

Abstract

Using a computational model of the Caenorhabditis elegans connectome dynamics, we show that proprioceptive feedback is necessary for sustained dynamic responses to external input. This is consistent with the lack of biophysical evidence for a central pattern generator, and recent experimental evidence that proprioception drives locomotion. The low-dimensional functional response of the Caenorhabditis elegans network of neurons to proprioception-like feedback is optimized by input of specific spatial wavelengths which correspond to the spatial scale of real body shape dynamics. Furthermore, we find that the motor subcircuit of the network is responsible for regulating this response, in agreement with experimental expectations. To explore how the connectomic dynamics produces the observed two-mode, oscillatory limit cycle behavior from a static fixed point, we probe the fixed point's low-dimensional structure using Dynamic Mode Decomposition. This reveals that the nonlinear network dynamics encode six clusters of dynamic modes, with timescales spanning three orders of magnitude. Two of these six dynamic mode clusters correspond to previously-discovered behavioral modes related to locomotion. These dynamic modes and their timescales are encoded by the network's degree distribution and specific connectivity. This suggests that behavioral dynamics are partially encoded within the connectome itself, the connectivity of which facilitates proprioceptive control.

摘要

利用秀丽隐杆线虫连接组动力学的计算模型,我们表明本体感受反馈对于对外界输入的持续动态反应是必要的。这与缺乏关于中枢模式发生器的生物物理证据以及最近关于本体感受驱动运动的实验证据是一致的。秀丽隐杆线虫神经元网络对类似本体感受反馈的低维功能反应通过对应于真实身体形状动态空间尺度的特定空间波长的输入进行优化。此外,我们发现网络的运动子电路负责调节这种反应,这与实验预期一致。为了探索连接组动力学如何从静态不动点产生观察到的双模式振荡极限环行为,我们使用动态模式分解探测不动点的低维结构。这揭示了非线性网络动力学编码了六个动态模式簇,其时间尺度跨越三个数量级。这六个动态模式簇中的两个对应于先前发现的与运动相关的行为模式。这些动态模式及其时间尺度由网络的度分布和特定连接性编码。这表明行为动力学部分编码在连接组本身内,其连接性有助于本体感受控制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b269/5226684/171b932209f6/pcbi.1005303.g001.jpg

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