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- W4307695978 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 textit{Aplysia californica} citep{shaw2015,lyttle2017}. We established in citep{WGCT2021} 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 textit{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." @default.
- W4307695978 created "2022-11-05" @default.
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- W4307695978 date "2022-05-17" @default.
- W4307695978 modified "2023-10-18" @default.
- W4307695978 title "Variational and phase response analysis for limit cycles with hard boundaries, with applications to neuromechanical control problems" @default.
- W4307695978 doi "https://doi.org/10.48550/arxiv.2205.08339" @default.
- W4307695978 hasPublicationYear "2022" @default.
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