About specific and general factors for visual illusions

Contrary to studies of audition and cognition, we previously did not find evidence for a general common factor for vision but for many very specific ones. For example, we found strong correlations between 19 versions of the Ebbinghaus illusion, which differed in color, shape, size or texture (N=87), suggesting a factor specific for the Ebbinghaus illusion. However, the Ebbinghaus illusion correlated very little with other illusions. Here, we tested whether illusion perception is orientation specific, similar to perceptual learning. We tested 5 illusions with 4 different orientations (N=20). While we found almost no inter-illusory correlations, most intra-illusory correlations were significant, i.e., susceptibility to an illusion does not seem to depend on its orientation. Contrary to perceptual learning, this finding provides further evidence for illusion-specific factors but not stimulus specific factors.\ The project was funded by Swiss National Science Foundation (SNSF), project "Learning from Delayed and Sparse Feedback" (CRSII2_147636).

Factors underlying visual illusions are illusion-specific but not feature-specific

Aline Françoise Cretenoud, Gregory Francis, Lukasz Grzeczkowski, Michael Herzog

Common factors are ubiquitous. For example, there is a common factor, g, for intelligence. In vision, there is much weaker evidence for such common factors. For example, visual illusion magnitudes correlate only weakly with each other. Here, we investigated whether illusions are hyper-specific as in perceptual learning. First, we tested 19 variants of the Ebbinghaus illusion that differed in color, shape, or texture. Correlations between the illusion magnitudes of the different variants were mostly significant. Second, we reanalyzed a dataset from a previous experiment where 10 illusions were tested under four conditions of luminance and found significant correlations between the different luminance conditions of each illusion. However, there were only very weak correlations between the 10 different illusions. Third, five visual illusions were tested with four orientations. Again, there were significant correlations between the four orientations of each illusion, but not across different illusions. The weak inter-illusion correlations suggest that there is no unique common mechanism for the tested illusions. We suggest that most illusions make up their own factor.

2019

Individual differences in visual (mis)perception: a multivariate statistical approach

Aline Françoise Cretenoud

Common factors are omnipresent in everyday life, e.g., people who do well in one cognitive test are likely to perform well in other cognitive tests as well, and vice versa. In vision, however, there seems to be a multitude of specific factors rather than a strong and unique common factor. For example, only weak correlations were observed between the susceptibility to different visual illusions, suggesting that the structure underlying visual illusions is multifactorial. In this thesis, I first examined the multidimensionality of the structure underlying visual illusions. To this aim, the susceptibility to various visual illusions was measured. In addition, subjects were tested with variants of the same illusion, which differed in spatial features, luminance, orientation, or contextual conditions. In line with previous work, only weak correlations were observed between the susceptibility to different visual illusions (i.e., between-illusion). An individual showing a strong susceptibility to one visual illusion does not necessarily show a strong susceptibility to other visual illusions. In contrast, there were strong correlations between the susceptibility to variants of the same illusion (i.e., within-illusion). Hence, factors seem to be illusion-specific but not feature-specific. In addition, the susceptibility to combinations of two illusions, which I call merged illusions, was measured to investigate how factors for illusions interact. The susceptibility to a merged illusion was strongly predicted from the susceptibility to the two illusions of which it was made, suggesting that factors for illusions combine independently to form complex illusory percepts. Second, I showed that individual differences in the perception of visual illusions are robust across the eye(s) to which the stimulus is presented, over a month, and when measured with an adjustment procedure or a method of constant stimuli. Last, I investigated whether a strong visual factor emerges in healthy elderly and patients with schizophrenia, which may be expected from the general decline in perceptual abilities usually reported in these two populations compared to healthy young adults. Similarly, a strong visual factor may emerge in action video gamers, who, contrary to healthy elderly and patients with schizophrenia, often show enhanced perceptual performance compared to non-video gamers. Hence, healthy elderly, patients with schizophrenia, and action video gamers were tested with a battery of visual tasks, such as a contrast detection and orientation discrimination task. As in control groups, between-task correlations were weak in general, which argues against the emergence of a strong common factor for vision in these populations. While similar tasks are usually assumed to rely on similar neural mechanisms, the performances in different visual tasks were only weakly related to each other, i.e., performance does not generalize across visual tasks. The results presented in this thesis highlight the relevance of an individual differences approach to unravel the multidimensionality of the visual structure.

EPFL2021

Individual differences in visual (mis)perception: a multivariate statistical approach

Aline Françoise Cretenoud

EPFL2021