Bilge Sayim¹, Olivia Koechli², Natalia Melnik³; ¹CNRS, University of Lille, ²ipw Winterthur, ³‪Otto-von-Guericke-University Magdeburg

In typical experiments on visual crowding (the deteriorating influence of clutter on target perception), observers are usually informed about the stimulus category they have to report. For example, observers are asked to report a target letter. This prior information strongly limits the response space to a few categorical (letter) responses, and may influence how targets are perceived. Here, we investigated to what extent prior experience with letter stimuli increased the likelihood to subsequently report letters when letter-like stimuli were presented. Targets consisted of letters and letter-like stimuli (modified letters with shortened and added lines), created with lines positioned on a virtual 3-by-3 dot grid. Targets were presented either in isolation or flanked by Xs (crowded) at 10° eccentricity to the left or right of fixation. Observers’ task was to capture target appearance by placing lines on a freely viewed response grid. There were two groups of observers: In the Letters First (LF) condition, observers were first presented with letters; in the Letters Second (LS) condition, observers were first presented with letter-like stimuli. We hypothesized that compared to the LS condition, the prior experience of letters in the LF condition would bias observers to report letters instead of the presented letter-like targets. We analyzed to what degree the appearance captures resembled the presented targets. The results showed strong deviations of the captured from the presented targets, especially when the targets were crowded. Quantifying how often observers reported the corresponding letter targets when presented with letter-like stimuli revealed that LF observers erroneously ‘corrected’ the letter-like stimuli to letters more frequently than LS observers. Overall, our results show that prior experience of letter stimuli strongly influenced appearance reports. We suggest that systematic biases in typical crowding paradigms can be revealed --and avoided-- by appearance-based methods.