ArticleBiological cybernetics2022
Variational and phase response analysis for limit cycles with hard boundaries, with applications to neuromechanical control problems.
Article in Biological cybernetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed, 8 citations in OpenAlex.
- Studying Synchronization of Neural Oscillators through NMDA-AMPA Receptor interactions.Chaos, solitons, and fractals · 2026Article
- NEURONpyxl: fast, flexible, Python-integrated simulation of biophysical neural networks with complex plastic synapses.Frontiers in computational neuroscience · 2026Article
- Incorporating buccal mass planar mechanics and anatomical features improves neuromechanical modeling of Aplysia feeding behavior.Biological cybernetics · 2025Article
- Tradeoffs in the energetic value of neuromodulation in a closed-loop neuromechanical system.Journal of theoretical biology · 2025Article
- Variational analysis of sensory feedback mechanisms in powerstroke-recovery systems.Biological cybernetics · 2024Article
- Tutorial: using NEURON for neuromechanical simulations.Frontiers in computational neuroscience · 2023Article
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Authors and funding
4 authors at 2 institutions in 1 country.
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Abstract
Motor systems show an overall robustness, but because they are highly nonlinear, understanding how they achieve robustness is difficult. In many rhythmic systems, robustness against perturbations involves response of both the shape and the timing of the trajectory. This makes the study of robustness even more challenging. To understand how a motor system produces robust behaviors in a variable environment, we consider a neuromechanical model of motor patterns in the feeding apparatus of the marine mollusk Aplysia californica (Shaw et al. in J Comput Neurosci 38(1):25-51, 2015; Lyttle et al. in Biol Cybern 111(1):25-47, 2017). We established in (Wang et al. in SIAM J Appl Dyn Syst 20(2):701-744, 2021. https://doi.org/10.1137/20M1344974 ) the tools for studying combined shape and timing responses of limit cycle systems under sustained perturbations and here apply them to study robustness of the neuromechanical model against increased mechanical load during swallowing. Interestingly, we discover that nonlinear biomechanical properties confer resilience by immediately increasing resistance to applied loads. In contrast, the effect of changed sensory feedback signal is significantly delayed by the firing rates' hard boundary properties. Our analysis suggests that sensory feedback contributes to robustness in swallowing primarily by shifting the timing of neural activation involved in the power stroke of the motor cycle (retraction). This effect enables the system to generate stronger retractor muscle forces to compensate for the increased load, and hence achieve strong robustness. The approaches that we are applying to understanding a neuromechanical model in Aplysia, and the results that we have obtained, are likely to provide insights into the function of other motor systems that encounter changing mechanical loads and hard boundaries, both due to mechanical and neuronal firing properties.
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