A Normalization Mechanism for Estimating Visual Motion across Speeds and Scales

Abstract

Interacting with the natural environment leads to complex stimulations of our senses. Here we focus on the estimation of visual speed, a critical source of 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 accurately infers 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” (CMCs) [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 channel combinations are activated. We developed a computational model demonstrating that the activity in a given channel is both boosted and weakened after 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 mechanism, a canonical principle that hitherto was found to operate mainly in early sensory processing. Overall, the speed-scale normalization mechanism may reflect the natural tendency of the visual system to integrate complex inputs into one coherent percept.