We disclose biologically plausible concepts to model swim center pattern generators in two sea slugs. We show how nonlinear reciprocation of cellular and synaptic dynamics underlies emergent network-level bursting. We discuss some of its prominent features including feed back loops to maintain stability of rhythm-generation, as well its resilience to short and long-term perturbations. Our research approaches are rooted in applied dynamical systems, parameter optimization with machine learning elements.
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