Abstract
In biology, the detection of visual motion is typically modeled via a set of elementary motion detectors (EMDs) forming a spatially distributed network. This paper summarizes recent results on estimating the dynamics of such an EMD construct from a biologically measured combination of their output signals. In particular, three interconnected problems pertaining to the field of system identification are treated. First, the visual stimuli design is discussed, namely the spatial excitation properties of multi-frequency sinusoidal gratings as these are typically utilized in biology. Second, the identification of EMD dynamics in the Laguerre domain from temporally restricted data sets is presented. Finally, a sparse optimization approach to the estimation of the weights of individual EMDs is described. The utilized design and estimation techniques are illustrated by simulation and experimental data from motion sensitive neurons in flies.
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