Nonlinear Control in the Nematode C. elegans

Recent whole-brain calcium imaging recordings of the nematode C. elegans have demonstrated that neural activity associated with behavior is dominated by dynamics on a low-dimensional manifold can be clustered according to behavioral states. Previous models either been linear models, which cannot support existence multiple fixed points in system, or Markov-switching do not describe how control signals produce switches between stable It remains unclear network neurons fast and slow timescale transitions states single model. We propose global, nonlinear model minimally parameterized captures state described dynamical system. The fit reproducing timeseries dominant PCA mode data. Long short time-scale changes transition statistics characterized via parameter Some these macro-scale experimental correlates neuro-modulators seem act as biological controls, allowing this generate testable hypotheses about effect global dynamics. theory provides an elegant characterization neuron population . Moreover, mathematical structure framework paradigm generalized more complex systems arbitrary number