title: Low-dimensional functionality of complex network dynamics: neurosensory integration in the Caenorhabditis Elegans connectome.
abstract: We develop a biophysical model of neurosensory integration in the model organism Caenorhabditis elegans. Building on experimental findings on the neuron conductances and their resolved connectome, we posit the first full dynamic model of the neural voltage excitations that allows for a characterization of network structures which link input stimuli to neural proxies of behavioral responses. Full connectome simulations of neural responses to prescribed inputs show that robust, low-dimensional bifurcation structures drive neural voltage activity modes. Comparison of these modes with experimental studies allows us to link these network structures to behavioral responses. Thus the underlying bifurcation structures discovered, i.e., induced Hopf bifurcations, are critical in explaining behavioral responses such as swimming and crawling.
authors.affiliation: Department of Physics, University of Washington, Seattle, Washington 98195, USA.
authors.forename: James
authors.initials: J
authors.lastname: Kunert
authors.affiliation: Department of Applied Mathematics, University of Washington, Seattle, Washington 98195-2420, USA.
authors.forename: Eli
authors.initials: E
authors.lastname: Shlizerman
authors.affiliation: Department of Applied Mathematics, University of Washington, Seattle, Washington 98195-2420, USA.
authors.forename: J Nathan
authors.initials: JN
authors.lastname: Kutz
mesh_terms: D000818:Animals; D017173:Caenorhabditis elegans / Q000502:physiology; D003198:Computer Simulation; D063132:Connectome / Q000379:methods*; D025461:Feedback, Physiological / Q000502:physiology; D008959:Models, Neurological; D009046:Motor Neurons / Q000502:physiology*; D009068:Movement / Q000502:physiology*; D009415:Nerve Net / Q000502:physiology*; D012677:Sensation / Q000502:physiology*