Time to wave good-bye to phase scrambling: creating controlled scrambled images using diffeomorphic transformations.

Abstract

To isolate the neural mechanisms associated with recognizing objects from those processing basic visual properties, control stimuli are required that contain the same perceptual properties as the objects but are unrecognizable. We demonstrate that conventional methods for generating control stimuli (phase scrambling, box scrambling, texture scrambling) yield poor controls because they dramatically distort the basic visual properties (e.g., spatial frequency, perceptual organization) to which even the earliest stages of visual processing are sensitive. We developed a new scrambling method, using a diffeomorphic transformation that preserves the basic perceptual properties of the image while removing meaning. We acquired perceptual ratings to determine the least amount of scrambling necessary to remove recognition. We hypothesized that our "diffeomorphic" images would produce neural activity at the earliest stages of the visual system that more closely matched activity in response to intact images relative to the other scrambling methods. To test this hypothesis, we used the HMAX computational model of object recognition and compared the simulated neural activity at the earliest stages of the visual system (layers S1, C1, and S2) between a set of 149 images scrambled using each distortion method to their intact version. We found that scrambled "diffeomorphed" images were indistinguishable to intact images in each layer of the model, but all of the other distortion methods yielded quite different patterns. Our results indicate that "diffeomorphed" images serve as more appropriate control stimuli in neuroimaging studies that aim to disentangle the representations of perceptual and semantic object properties.