Wide-Field, Motion-Sensitive Neurons and Optimal Matched Filters for Optic Flow

. We present a theory for the construction of an optimal matched #lter for self-motion induced optic #ow #elds. The matched #lter extracts local #ow components along a set of pre-de#ned directions and weights them according to an optimization principle which minimizes the di#erence between estimated and real egomotion parameters. In contrast to previous approaches, prior knowledge about distance and translation statistics is incorporated in the form of a #world model". Simulations indicate that the matched #lter model yields reliable self-motion estimates. A comparison of the weight distribution used in the model with the local motion sensitivities of individual and small groups of interneurons in the #y visual system shows a close correspondence. This suggests that these so-called tangential neurons are tuned to optic #ow #elds induced by rotation or translation along a particular axis. They seem to weight the local optic #ow according to the contribution of input noise and the expect..