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Lern- und Qualifikationsziele Beherrschung theoretischer Methoden zur Beschreibung der stochastischen Aktivität und Signalübertragung von Neuronen Voraussetzungen Interesse an interdisziplinärer Forschung und dem Gebrauch stochastischer Modelle in den Neurowissenschaften
Gliederung / Themen / Inhalte Key concepts from nonlinear dynamics (bifurcations, fixed points, manifolds, limit cycle), stochastic processes (Langevin and Fokker-Planck equations, Master equation, linear response theory), information theory (mutual information and its lower and upper bounds), point processes (Poisson process; renewal vs. nonrenewal point process). Neural noise sources and how they enter different neuron models, the diffusion approximation of synaptic input or channel fluctuations by a Gaussian noise, measures of spike train and interval variability and their interrelation, Poisson spike train: entropy & information content, one-dimensional stochastic integrate-and-fire (IF) neurons: spontaneous activity, response to weak stimuli & information transfer, different forms of stochastic resonance in single neurons and neuronal populations, multidimensional IF models: subthreshold resonances, synaptic filtering & spike-frequency adaptation, effect of nonrenewal behavior of the spontaneous activity on the information transfer, outlook: stimulus-driven correlations; networks of stochastic neurons.
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