The transsaccadic feature prediction mechanism associates peripheral and foveal information belonging to the same object to make predictions about how an object seen in the periphery would appear in the fovea or vice versa. It is unclear if such transsaccadic predictions require experience with the object such that only familiar objects benefit from this mechanism by virtue of having peripheral-foveal associations. In two experiments, we tested whether familiar objects have an advantage over novel objects in peripheral-foveal matching and transsaccadic change detection tasks. In both experiments, observers were unknowingly familiarized with a small set of stimuli by completing a sham orientation change detection task. In the first experiment, observers subsequently performed a peripheral-foveal matching task, where they needed to pick the foveal test object that matched a briefly presented peripheral target. In the second experiment, observers subsequently performed a transsaccadic object change detection task where a peripheral target was exchanged or not exchanged with another target after the saccade, either immediately or after a 300-ms blank period. We found an advantage of familiar objects over novel objects in both experiments. While foveal-peripheral associations explained the familiarity effect in the matching task of the first experiment, the second experiment provided evidence for the advantage of peripheral-foveal associations in transsaccadic object change detection. Introducing a postsaccadic blank improved change detection performance in general but more for familiar than for novel objects. We conclude that familiar objects benefit from additional object-specific predictions.

Softness is an important material property that can be judged directly, by interacting with an object, but also indirectly, by simply looking at an image of a material. The latter is likely possible by filling in relevant multisensory information from prior experiences with soft materials. Such experiences are thought to lead to associations that make up our representations about perceptual softness. Here, we investigate the structure of this representational space when activated by words, and compare it to haptic and visual perceptual spaces that we obtained in earlier work. To this end, we performed an online study where people rated different sensory aspects of soft materials, presented as written names. We compared the results with the previous studies where identical ratings were made on the basis of visual and haptic information. Correlation and Procrustes analyses show that, overall, the representational spaces of verbally presented materials were similar to those obtained from haptic and visual experiments. However, a classifier analysis showed that verbal representations could better be predicted from those obtained from visual than from haptic experiments. In a second study we rule out that these larger discrepancies in representations between verbal and haptic conditions could be due to difficulties in material identification in haptic experiments. We discuss the results with respect to the recent idea that at perceived softness is a multidimensional construct.

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