Background: Recent claims in neuroscience and evolutionary biology suggest that the aesthetic sense reflects preferences for image signals whose characteristics best fit innate brain mechanisms of visual recognition.

Results: This hypothesis was tested by behaviourally measuring, for a set of initially unfamiliar images, the effects of category learning on preference judgements by humans, and by relating the observed data to computationally reconstructed internal representations of categorical concepts. Category learning induced complex shifts in preference behaviour. Two distinct factors - complexity and bilateral symmetry - could be identified from the data as determinants of preference judgements. The effect of the complexity factor varied with object knowledge acquired through category learning. In contrast, the impact of the symmetry factor proved to be unaffected by learning experience. Computer simulations suggested that the preference for pattern complexity relies on active (top-down) mechanisms of visual recognition, whereas the preference for pattern symmetry depends on automatic (bottom-up) mechanisms.

Conclusions: Human visual preferences are not fully determined by (objective) structural regularities of image stimuli but also depend on their learned (subjective) interpretation. These two aspects are reflected in distinct complementary factors underlying preference judgements, and may be related to complementary modes of visual processing in the brain.