Can fly tangential neurons be used to estimate self-motion?

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Abstract
The so-called tangential neurons in the fly brain are sensitive to the typical optic flow patterns generated during self-motion. This suggests a possible involvement in the self-motion estimation process. In this study, we examine whether a simplified matched filter model of these neurons can be used to estimate self-motion from the optic flow. We present a theory for the construction of an optimal matched filter incorporating both the noise properties of the motion signal, and prior knowledge about the distance distribution of the invironment. Tests on a mobile robot demonstrate that the matched filter approach works for real time camera input and the noisy motion fields computed by Reichardt motion detectors

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