Visual stimuli are known to vary in their perceived duration, with some stimuli engendering so-called “time dilation” and others “time compression” effects, in which stimuli appear to last for relatively longer or shorter durations, respectively. Extant theories have suggested these effects rely on the level of attention devoted to stimuli, the magnitude of the stimulus, or the intensity of the neural response, yet none of these can fully account for the observed effects. Recently, we demonstrated that perceived time is dilated by the memorability of an image (Ma, et al. 2024). To explain the memorability effect, we found that a recurrent convolutional neural network (rCNN) could recapitulate the time dilation effect by indexing the rate of entropy decline, or “speed”, across successive timesteps, with more memorable images associated with faster speeds. Here, we replicate and extend these findings by applying this model to a wider array of images and testing three groups of subjects (n = 20ea.) on images sampled according to their speed, memorability, or both. We found that images that increased in speed, but with constant memorability, or images that increased in memorability, but with constant speed, both dilated perceived time, and further found that speed alone could induce a shift in 24h memory recognition performance of ~17%. However, we also found that images with very fast speeds exhibited an opposite, time compression effect. These findings can be explained by a simple inverted-U model between speed and perceived duration that scales with the memorability of the image. Overall, our findings provide the boundaries of speed and memorability effects on time perception, suggesting the visual system dilates time when presented with informative stimuli but compresses it when these stimuli become overwhelmingly complex.
Wiener et al. (Mon,) studied this question.