Time^2: A framework for the neural dynamics of visual perception

Abstract

Whenever we look at an object, we seem to perceive it immediately. However, this is not the case for two reasons. First, it takes hundreds of milliseconds for the brain to process visual information reaching the retina. Second, we have to look at an object for a certain amount of time to perceive it (and we typically look at it for hundreds of milliseconds) -- during that time, visual information is continuously received on our retinas. These facts together imply that visual information is both processed and received through time. These two temporal facets of perception, which we term processing time and stimulus time, are often conflated in the literature. Moreover, processing time and stimulus time are usually not considered together in experiments. Here, we argue that, to obtain a more complete portrait of visual perception and constrain further models of vision, it is essential to consider and measure both temporal facets simultaneously. We present a new method designed to do so that is based on reverse correlation: Time^2. We show that this method allows us to precisely characterize many neural phenomena, including rhythmic perception, predictive processing and coarse-to-fine sampling.