Local and global responses of insect motion detectors to the spatial structure of natural scenes

As a consequence of the non-linear correlation mechanism underlying motion detection, the variability in local pattern structure and contrast inherent within natural scenes profoundly influences local motion responses. To accurately interpret optic flow induced by self-motion, neurons in many dipteran flies smooth this "pattern noise" by wide-field spatial integration. We investigated the role that size and shape of the receptive field plays in smoothing out pattern noise in two unusual hoverfly optic flow neurons: one (HSN) with an exceptionally small receptive field and one (HSNE) with a larger receptive field. We compared the local and global responses to a sequence of panoramic natural images in these two neurons with a parsimonious model for elementary motion detection weighted for their spatial receptive fields. Combined with manipulation of size and contrast of the stimulus images, this allowed us to separate spatial integration properties arising from the receptive field, from other local and global non-linearities, such as motion adaptation and dendritic gain control. We show that receptive field properties alone are poor predictors of the response to natural scenes. If anything, additional non-linearity enhances the pattern dependence of HSN's response, particularly to vertically elongated features, suggesting that it may serve a role in forward fixation during hovering.