Delaram Farzanfar¹ (), Morteza Rezanejad¹, Dirk B. Walther¹; ¹Department of Psychology, University of Toronto

The experience of aesthetic pleasure is associated with reward-processing mechanisms in the human brain. Previous studies show that visual attention is biased towards objects associated with higher value in the environment. We investigate the relationship between natural gaze patterns and aesthetic valuations of scenes. To assess the contribution of salience-driven and reward-driven biases toward attentional allocation, we develop a model of gaze patterns that combines low-level, stimulus-driven salience with the aesthetic value of image regions. Our results show a positive relationship between gaze activity and aesthetic value. Moreover, we observe strong similarities in the spatial distribution of highly salient proto-object regions and scene regions with high aesthetic value, suggesting that salience plays an important role in evaluating the potential hedonic value of visual features. We further probe the relationship between intermediate-level representations of objects and aesthetic value by repurposing a deep neural network trained on object categorization to predict aesthetic value. We do this by replacing the top layer of the VGG-16 architecture with a linear layer with weights adjusted to predict aesthetic liking. Notably, the network weights in all layers except the new linear top layer are left unchanged. This network predicts subjective aesthetic valuations of scenes with high accuracy. This result highlights the intricate relationships between hedonic value, salience, and object perception. We hypothesize that expected hedonic value can function as the incentive to focus attention on salient image locations, likely to contain objects with ecological value. Rather than being a separate, affective visual process, aesthetic valuation is tightly intertwined with other aspects of visual cognition, such as attention and object recognition.

Acknowledgements: NSERC