A Normalization Mechanism for Estimating Visual Motion across Speeds and Scales.

Abstract

The use of simple stimuli has been tremendously beneficial to understand the basic properties of primary sensory systems. However, interacting with the natural environment leads to complex stimulations of our senses. Here we focus on the estimation of visual speed, a critical information for the survival of many animal species as they monitor moving prey or approaching dangers. In mammals, and in particular in primates, speed information is conceived to be represented by a set of channels sensitive to different spatial and temporal characteristics of the optic flow [1-5]. However, it is still largely unknown how the brain could accurately infer the speed of complex natural scenes from this set of spatiotemporal channels [6-14]. As complex stimuli, we chose a set of well-controlled moving naturalistic textures called 'Compound Motion Clouds' (CMC) [15, 16] that simultaneously activate multiple spatiotemporal channels. We found that CMC stimuli that have the same physical speed are perceived moving at different speeds depending on which channels are activated. Thanks to a computational model, we show that the activity in a given channel is both boosted and weakened following a systematic pattern over neighboring channels. This pattern of interactions can be understood as a combination of two components oriented in speed (consistent with a slow-speed prior) and scale (sharpening of similar features). Interestingly, the interaction along scale implements a lateral inhibition principle that is usually found to operate in early sensory processing. These results further promote the idea that lateral inhibition along a variety of dimensions is a canonical principle of perceptual processing. Overall, the speed-scale normalization mechanism may reflect the natural tendency of the visual system to integrate complex inputs into one coherent percept.