MBI Videos

Casey Diekman

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    Casey Diekman
    Modern data assimilation (DA) techniques are widely used in climate science and weather prediction but have only recently begun to be applied in neuroscience. In this talk I will illustrate the use of DA algorithms to estimate unobserved variables and unknown parameters of conductance-based neuronal models and propose the bifurcation structure of inferred models as a qualitative measure of estimation success. I will then apply DA to electrophysiological recordings from suprachiasmatic nucleus neurons to develop models that provide insight into the functioning of the mammalian circadian clock. Finally, I will frame the selection of stimulus waveforms to inject into neurons during patch-clamp recordings as an optimal experimental design problem and present preliminary results on the optimal stimulus waveforms for improving the identifiability of parameters for a Hodgkin-Huxley-type model.
  • video photo
    Casey Diekman

    The mechanisms underlying oscillations in a central pattern generator (CPG) may differ fundamentally in the intact organism versus an isolated CPG preparation. We investigate this aspect of rhythmogenesis in a computational model of closed-loop respiratory control, incorporating minimal models of the brainstem CPG, lung mechanics, oxygen handling, metabolism, and chemosensation. We analyze the model behavior using fast/slow dynamical systems analysis and open-loop/closed-loop control analysis. We show that eupnea-like bursting oscillations arise from a distinct mechanism in the intact (closed loop) versus isolated (open loop) systems. The closed-loop model exhibits bistability between eupnea-like bursting and tachypnea-like tonic spiking, and we demonstrate that imposed bouts of hypoxia can induce a dramatic transition from eupnea to tachypnea. For moderate bouts of hypoxia, the endogenous properties of the ionic conductances in the Butera-Rinzel-Smith CPG model can lead to spontaneous autoresuscitation and recovery to eupnea. We also find that chemosensory feedback gives the closed-loop control system greater robustness to changes in metabolic demand than the open-loop control system.

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