The visual system can predict visual features across saccades based on learned transsaccadic associations between peripheral and foveal input. This has been shown for simple visual features such as shape, size, and spatial frequency. The present study investigated whether transsaccadic predictions are also made for more complex visual stimuli. In an acquisition phase, new transsaccadic associations were established. In the first experiment, pictures of real-world objects changed category during the saccade (fruits were changed into balls or vice versa). In the second experiment, the gender of faces was manipulated during the saccade (faces changed from male to female or vice versa). In the following test phase, the stimuli were briefly presented in the periphery, and participants had to indicate which object or face, respectively, they had perceived. In both experiments, peripheral perception was biased toward the acquired associated foveal input. These results demonstrate that transsaccadic predictions are not limited to a small set of simple visual features but can also be made for more complex and realistic stimuli. Multiple new associations can be learned within a short time frame, and the resulting predictions appear to be object specific.

Faced with inhomogeneous representations, the visual system has to rely on pre- and postsaccadic processing mechanisms to assure perceptual continuity across eye movements. While postsaccadically, memorized peripheral and postsaccadic foveal information are integrated according to their reliabilities, here we investigated whether this also holds true for the presaccadic combination of peripheral input and internal associated foveal images. In three experiments, participants learned associations between objects changing transsaccadically in one feature dimension (spatial frequency in Experiment 1 and color in Experiments 2 and 3). Subsequently, participants judged the respective feature of only peripherally presented objects. Importantly, the reliability of this peripheral input was manipulated by lowering the contrast (Experiment 1) or adding color noise (Experiment 3). We hypothesized that participants’ presaccadic peripheral percepts would be biased toward the internal associated foveal image and that the biasing effect would be stronger the lower the peripheral reliability. In all experiments, perception was biased in the direction of the associated foveal image. However, the strength of the bias did not differ between reliability conditions. The presaccadic perceptual bias effect had previously not been tested with the feature color. By showing that yet another feature incorporates prior transsaccadic knowledge, our results highlight the scope of the effect. Furthermore, they point to important differences between pre- and postsaccadic processing mechanisms.

Humans incorporate knowledge of transsaccadic associations into peripheral object perception. Several studies have shown that learning of new manipulated transsaccadic associations leads to a presaccadic perceptual bias. However, there was still disagreement whether this learning effect was location specific (Herwig, Weiß, & Schneider, 2018) or generalizes to new locations (Valsecchi & Gegenfurtner, 2016). The current study investigated under what conditions location generalization of transsaccadic learning occurs. In all experiments, there were acquisition phases in which the spatial frequency (Experiment 1) or the size (Experiment 2 and 3) of objects was changed transsaccadically. In the test phases, participants judged the respective feature of peripheral objects. These could appear either at the location where learning had taken place or at new locations. All experiments replicated the perceptual bias effect at the old learning locations. In two experiments, transsaccadic learning remained location specific even when learning occurred at multiple locations (Experiment 1) or with the feature of size (Experiment 2) for which a transfer had previously been shown. Only in Experiment 3 was a transfer of the learning effect to new locations observable. Here, learning only took place for one object and not for several objects that had to be discriminated. Therefore, one can conclude that, when specific associations are learned for multiple objects, transsaccadic learning stays location specific and when a transsaccadic association is learned for only one object it allows a generalization to other locations.

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