Time to wave goodbye to phase scrambling - creating unrecognizable control stimuli using a diffeomorphic transform.

To isolate the neural events associated with the recognition of visual objects from the events corresponding to the perceptual processing prior to object recognition, control stimuli are needed that contain the same perceptual properties as the objects, but are not recognizable. Traditionally, control stimuli have been generated using phase-scrambling, box scrambling, and more recently, texture scrambling. We show these methods yield poor control stimuli because they dramatically change basic visual properties (e.g., spatial frequency, perceptual organization) to which even the earliest stages of visual processing are sensitive. To overcome this limitation, we applied a new warping method, using a diffeomorphic transformation that preserves lower-level perceptual properties while removing meaning; we acquired norms for recognition at various degrees of warping (N=415 participants completed 15600 trials). We hypothesized that images warped using our new method will produce neural activity at pre-recognition stages along the visual hierarchy that is similar to the intact versions of these images. To test this hypothesis, we computationally modeled neural activity (using the HMAX model) for each distortion method and compared it to the intact version of the image at three stages along the visual system: simple and complex V1 cells, anterior areas corresponding to area V4, and inferior temporal cortex. Based on average neural output and the distribution of activity across simulated neurons, we found that "diffeomorphed images" were markedly more similar to intact images than any of the other distortion methods. Our results show that unrecognizable diffeomorphed images better match the fundamental visual properties of intact images, and therefore serve as more appropriate control stimuli in neuroimaging research. We suggest that diffeomorphed images should be used to disentangle the representation of perceptual and semantic object features during perception, memory and attention. Meeting abstract presented at VSS 2013