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The processing and perception of visual stimuli are greatly dependent on the context in which those stimuli are presented. While this is not always (and indeed is probably not "supposed" to be) evident when viewing real-world scenes, the abundance of contextual effects is revealed for example by the vast number of different visual illusions. Context can profoundly change the way the visual system processes single visual stimuli. In contrast masking, surround suppression, and crowding, distracting stimuli impair the observer's ability to detect, identify, and make other judgements about visual stimuli. These perceptual phenomena presumably reflect the operation of neural mechanisms that adjust the "operating range" of the visual system according to the prevailing conditions, or act to reduce responses to redundant stimulus features. This work first investigates the relationship between masking, which is caused by stimuli that are spatially superimposed on a target stimulus, and surround suppression, which is caused by spatially displaced stimuli. This was done using a temporal masking paradigm and measuring the time-courses of masking and surround suppression. The results reveal how the effects of these suppressive interactions are delicately dependent on stimulus timing and suggest that surround suppression acts extremely fast, having an effect on the early part of the neural response. Finally, contextual effects such as surround suppression and crowding are often considered to be "automatic" processes that occur over fixed areas in the visual field. The final part of this work shows how changing the spatial layout, and consequently the perceptual organization, of the stimuli can dramatically reduce surround suppression and crowding effects, even in conditions where the current models would predict strong effects. Surround suppression and crowding seem to operate only within perceptually homogeneous areas, while stimuli that are perceptually separate, the ones that "stand out", are not affected.
Silvestro Micera, Daniela De Luca