Shared and Distinct Genetic Sources of Variability in Visual Aesthetic Value

Bignardi, Giacomo; Lf, Ticini; Smit, D; Polderman, Tinca J. C.

doi:10.31234/osf.io/79nbq

Cited by 5 publications

(4 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We can only speculate about the origins of the remaining variance, which is not covered by the SIPs. Besides higher-order visual features, possible sources of variance include environmental and genetic factors ( Bignardi et al, 2020 ; for a review, see Chamberlain, 2022 ), as also found for the evaluation of face attractiveness ( Germine et al, 2015 ). Personality factors also predict aesthetic ratings ( Chamorro-Premuzic, 2009 ).…”

Section: Discussionmentioning

confidence: 99%

Statistical image properties predict aesthetic ratings in abstract paintings created by neural style transfer

et al. 2022

View full text Add to dashboard Cite

Artificial intelligence has emerged as a powerful computational tool to create artworks. One application is Neural Style Transfer, which allows to transfer the style of one image, such as a painting, onto the content of another image, such as a photograph. In the present study, we ask how Neural Style Transfer affects objective image properties and how beholders perceive the novel (style-transferred) stimuli. In order to focus on the subjective perception of artistic style, we minimized the confounding effect of cognitive processing by eliminating all representational content from the input images. To this aim, we transferred the styles of 25 diverse abstract paintings onto 150 colored random-phase patterns with six different Fourier spectral slopes. This procedure resulted in 150 style-transferred stimuli. We then computed eight statistical image properties (complexity, self-similarity, edge-orientation entropy, variances of neural network features, and color statistics) for each image. In a rating study, we asked participants to evaluate the images along three aesthetic dimensions (Pleasing, Harmonious, and Interesting). Results demonstrate that not only objective image properties, but also subjective aesthetic preferences transferred from the original artworks onto the style-transferred images. The image properties of the style-transferred images explain 50 – 69% of the variance in the ratings. In the multidimensional space of statistical image properties, participants considered style-transferred images to be more Pleasing and Interesting if they were closer to a “sweet spot” where traditional Western paintings (JenAesthetics dataset) are represented. We conclude that NST is a useful tool to create novel artistic stimuli that preserve the image properties of the input style images. In the novel stimuli, we found a strong relationship between statistical image properties and subjective ratings, suggesting a prominent role of perceptual processing in the aesthetic evaluation of abstract images.

show abstract

Section: Discussionmentioning

confidence: 99%

Statistical image properties predict aesthetic ratings in abstract paintings created by neural style transfer

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Barron and Parisi's (1976) results, therefore, questioned Barron's (1972) earlier results, and suggested that genetics has little impact on both of these measures of aesthetic judgment. Despite this contradiction in results, these studies showed the promise for a behavioral genetics of aesthetic appreciation (Bignardi et al, 2020). (1940 -) corroborated and extended these conclusions in a series of experiments: high-school and college students who are more creative prefer more complex polygonal figures and find them more meaningful than less creative peers (R. Eisenman & Robinson, 1967;R E Taylor & Eisenman, 1964).…”

Section: Simplicity-complexity As a Factor Of Perceptual Preferencementioning

confidence: 84%

“…MZ twins are genetically identical, and DZ twins are on average 50% identical. Comparing the degree of similarity in the performance of MZ and DZ pairs on tests of a certain capacity allows estimating the impact of genetics on that capacity: If the performance of MZ twins is more similar than the performance of DZ, it can be assumed that genetics has a strong influence on that capacity (Bignardi, Ticini, Smit, & Polderman, 2020). Barron (1972) tested 59 pairs of Italian twins, 30 MZ and 29 DZ, and 57 pairs of American twins, 29 MZ and 28 DZ, on several measures of creative thinking and aesthetic appreciation, including the Barron-Welsh Art Scale as a measure of preference for complexity (F. X.…”

Section: Simplicity-complexity As a Factor Of Perceptual Preferencementioning

confidence: 99%

One hundred years of Empirical Aesthetics: Fechner to Berlyne (1876 – 1976)

Nadal¹,

Ureña²

2021

Preprint

View full text Add to dashboard Cite

In this chapter, we review the history of Empirical Aesthetics since its foundation byFechner in 1876 to Berlyne’s New Empirical Aesthetics in the 1970s. We explain whyand how Fechner founded the field, and how Wundt and Müller’s students continued hiswork in the early 20th century. In the United States, Empirical Aesthetics flourished aspart of American functional psychology at first, and later as part of behaviorists’ interestin reward value. The heyday of behaviorism was also a golden age for the developmentof all sorts of tests for artistic and aesthetic aptitudes. We end the chapter covering thecontributions of Gestalt psychology and Berlyne’s motivational theory to EmpiricalAesthetics.

show abstract

“…The aetiology of these individual differences can be attributed to multiple sources. Behavioural genetic research implies that variation in genes account for a limited proportion (approximately 30%) of the variance in perceived facial attractiveness (Germine et al, 2015), and a similar proportion of the variance in the intensity of aesthetic appraisal of abstract objects and scenes (Bignardi et al, 2020). The remaining variation likely lies within unique environmental factors, due to individual differences in exposure and enculturation.…”

Section: Considering the Interplay Between Objective And Subjective A...mentioning

confidence: 99%

The Interplay of Objective and Subjective Factors in Empirical Aesthetics

Chamberlain

2022

Human Perception of Visual Information

View full text Add to dashboard Cite

The field of empirical aesthetics sets out to understand and predict our aesthetic preferences . Its history dates back to the birth of visual psychophysics and the work of Gustav Fechner (1876), while multiple models of aesthetic experience have been proposed in the intervening years (Chatterjee & Vartanian, 2014;Leder et al., 2004;Pelowski et al., 2017). This chapter briefly sets out the history of empirical aesthetics, and the state of the research field at present. I outline recent work on inter-observer agreement in aesthetic preference, before presenting empirical work that argues the importance of first objective (characteristics of stimuli) and then subjective (characteristics of context) factors in shaping aesthetic preference. Considering the role of properties of the stimulus, I will review literature on the relationship between aesthetic preference and symmetry, shape, compositional structure, colour and complexity as well as considering the potential role of statistical properties of images. I will then review putative subjective predictors of aesthetic preference including the role of context, framing and the influence of information about the artist and the artistic process. Both subjective and objective approaches will be evaluated from an individual differences perspective, focusing on the mediating role of familiarity, expertise, culture, cognitive ability and personality. Finally, I will attempt to draw these approaches together with reference to aesthetic sensitivity: an individual observer's propensity to have an aesthetic response to a particular objective image characteristic, and will explore some putative factors that may modulate and explain individual differences in aesthetic sensitivity.providing the foundation for later efforts to establish lawful relationships between stimulus properties and aesthetic preferences (Birkhoff, 1933;Eysenck, 1940) with reference to psychobiological mechanisms of arousal (Berlyne, 1974). Such efforts focused on the predictive value of low-level stimulus properties, such as colour, symmetry, proportion, contrast, contour, and later on collative properties such as order, complexity and ambiguity (Berlyne, 1974). Such an approach remains common in empirical aesthetics. However, more recent research in the field has placed focus on sensory and cognitive processing dynamics, modelling how observers respond to salient properties of the stimulus (Flavell et al., 2020;Reber et al., 2004), but also incorporating the sensory and cognitive history of the observer (Cutting, 2003;Zajonc, 1968). The latter approach highlights the critical role subjective aspects such as context and exposure play in shaping our aesthetic experiences. Objective and subjective perspectives have been brought together in comprehensive aesthetic models in recent years, bringing both psychological and neuroscientific understanding to the numerous objective and subjective mechanisms identified by researchers in the field (

show abstract

Shared and Distinct Genetic Sources of Variability in Visual Aesthetic Value

Cited by 5 publications

References 37 publications

Statistical image properties predict aesthetic ratings in abstract paintings created by neural style transfer

Statistical image properties predict aesthetic ratings in abstract paintings created by neural style transfer

One hundred years of Empirical Aesthetics: Fechner to Berlyne (1876 – 1976)

The Interplay of Objective and Subjective Factors in Empirical Aesthetics

Contact Info

Product

Resources

About