Spatiotemporal Feedback and Network Structure Drive and Encode Caenorhabditis elegans Locomotion

• Published in: PLoS computational biology 2017-01, Vol.13 (1), p.e1005303-e1005303
• Main Authors: Kunert, James M, Proctor, Joshua L, Brunton, Steven L, Kutz, J Nathan
• Format: Article
• Language: English
• Subjects: Animals; Behavior; Biology and Life Sciences; Caenorhabditis elegans; Caenorhabditis elegans - physiology; Colleges & universities; Computational Biology; Computer and Information Sciences; Connectome; Feedback; Feedback, Physiological - physiology; Funding; Locomotion - physiology; Medicine and Health Sciences; Models, Neurological; Nematodes; Neural circuitry; Neurons; Neurons - physiology; Physiological aspects; Proprioception; Research and Analysis Methods; Social Sciences
• ISSN: 1553-7358; 1553-734X; 1553-7358
• DOI: 10.1371/journal.pcbi.1005303

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.