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Neuronal morphology plays a fundamental role for the information processing capabilities of neurons. These dependencies can be investigated using compartmental models to simulate functional properties of morphologically characterized neurons. We developed an automated system to investigate the effect of realistic morphologies on the electrophysiological properties of a neuron and applied it to morphologies of neurons of the medial superior olive (MSO) from published data (Rautenberg et al., 2009). The simulation paradigm was designed to be in accordance with electrophysiological experiments conducted by Scott et al.(2005), concerning measurements of input resistance and effective membrane time constant. Simulating neurons from morphological data using compartmental models implies a highly complex parameter space, both in terms of the simulation parameters and the results. To cope with this …