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Beauty and the beholder: the role of visual sensitivity in visual preference.

Spehar B, Wong S, van de Klundert S, Lui J, Clifford CW, Taylor RP - Front Hum Neurosci (2015)

Bottom Line: We measure sensitivity to simple visual patterns (sine-wave gratings varying in spatial frequency and random textures with varying scaling exponent) and find that they are highly correlated with visual preferences exhibited by the same observers.Although we do not attempt to offer a comprehensive neural model of aesthetic experience, we demonstrate a strong relationship between visual sensitivity and preference for simple visual patterns.Broadly speaking, our results support assertions that there is a close relationship between aesthetic experience and the sensory coding of natural stimuli.

View Article: PubMed Central - PubMed

Affiliation: School of Psychology, UNSW Australia Sydney, NSW, Australia.

ABSTRACT
For centuries, the essence of aesthetic experience has remained one of the most intriguing mysteries for philosophers, artists, art historians and scientists alike. Recently, views emphasizing the link between aesthetics, perception and brain function have become increasingly prevalent (Ramachandran and Hirstein, 1999; Zeki, 1999; Livingstone, 2002; Ishizu and Zeki, 2013). The link between art and the fractal-like structure of natural images has also been highlighted (Spehar et al., 2003; Graham and Field, 2007; Graham and Redies, 2010). Motivated by these claims and our previous findings that humans display a consistent preference across various images with fractal-like statistics, here we explore the possibility that observers' preference for visual patterns might be related to their sensitivity for such patterns. We measure sensitivity to simple visual patterns (sine-wave gratings varying in spatial frequency and random textures with varying scaling exponent) and find that they are highly correlated with visual preferences exhibited by the same observers. Although we do not attempt to offer a comprehensive neural model of aesthetic experience, we demonstrate a strong relationship between visual sensitivity and preference for simple visual patterns. Broadly speaking, our results support assertions that there is a close relationship between aesthetic experience and the sensory coding of natural stimuli.

No MeSH data available.


Box and whisker plots of individual correlations between discrimination sensitivity and preference for 46 observers. The 25–75% quartiles of the distribution are drawn using a box. The median is shown with a horizontal line inside the box. Maximum “whisker” length corresponds to 1.5 *Interquartile range (25–75). This value corresponds approximately to ± 2.7 SD and 99.3% coverage. The points outside of this range are considered outliers.
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Figure 7: Box and whisker plots of individual correlations between discrimination sensitivity and preference for 46 observers. The 25–75% quartiles of the distribution are drawn using a box. The median is shown with a horizontal line inside the box. Maximum “whisker” length corresponds to 1.5 *Interquartile range (25–75). This value corresponds approximately to ± 2.7 SD and 99.3% coverage. The points outside of this range are considered outliers.

Mentions: The correlation between the average discrimination sensitivity and visual preference for the Grayscale images was quite high with Pearson r equaling 0.738 (p < 0.023). However, in order to establish whether the association sensitivity and preference exist beyond level of average results, we calculated the average of individual correlation coefficients across 46 observers. The average individual correlations between discrimination sensitivity and preference for 46 participants equaled 0.267 (95% CI = 0.127–0.406, p < 0.0004). Figure 7 depicts the box and whiskers plot of individual correlation coefficients between discrimination sensitivity and preference data for 46 individual observers. As indicated in this figure, the median of individual correlations between discrimination sensitivity and visual preference was 0.378.


Beauty and the beholder: the role of visual sensitivity in visual preference.

Spehar B, Wong S, van de Klundert S, Lui J, Clifford CW, Taylor RP - Front Hum Neurosci (2015)

Box and whisker plots of individual correlations between discrimination sensitivity and preference for 46 observers. The 25–75% quartiles of the distribution are drawn using a box. The median is shown with a horizontal line inside the box. Maximum “whisker” length corresponds to 1.5 *Interquartile range (25–75). This value corresponds approximately to ± 2.7 SD and 99.3% coverage. The points outside of this range are considered outliers.
© Copyright Policy
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4585069&req=5

Figure 7: Box and whisker plots of individual correlations between discrimination sensitivity and preference for 46 observers. The 25–75% quartiles of the distribution are drawn using a box. The median is shown with a horizontal line inside the box. Maximum “whisker” length corresponds to 1.5 *Interquartile range (25–75). This value corresponds approximately to ± 2.7 SD and 99.3% coverage. The points outside of this range are considered outliers.
Mentions: The correlation between the average discrimination sensitivity and visual preference for the Grayscale images was quite high with Pearson r equaling 0.738 (p < 0.023). However, in order to establish whether the association sensitivity and preference exist beyond level of average results, we calculated the average of individual correlation coefficients across 46 observers. The average individual correlations between discrimination sensitivity and preference for 46 participants equaled 0.267 (95% CI = 0.127–0.406, p < 0.0004). Figure 7 depicts the box and whiskers plot of individual correlation coefficients between discrimination sensitivity and preference data for 46 individual observers. As indicated in this figure, the median of individual correlations between discrimination sensitivity and visual preference was 0.378.

Bottom Line: We measure sensitivity to simple visual patterns (sine-wave gratings varying in spatial frequency and random textures with varying scaling exponent) and find that they are highly correlated with visual preferences exhibited by the same observers.Although we do not attempt to offer a comprehensive neural model of aesthetic experience, we demonstrate a strong relationship between visual sensitivity and preference for simple visual patterns.Broadly speaking, our results support assertions that there is a close relationship between aesthetic experience and the sensory coding of natural stimuli.

View Article: PubMed Central - PubMed

Affiliation: School of Psychology, UNSW Australia Sydney, NSW, Australia.

ABSTRACT
For centuries, the essence of aesthetic experience has remained one of the most intriguing mysteries for philosophers, artists, art historians and scientists alike. Recently, views emphasizing the link between aesthetics, perception and brain function have become increasingly prevalent (Ramachandran and Hirstein, 1999; Zeki, 1999; Livingstone, 2002; Ishizu and Zeki, 2013). The link between art and the fractal-like structure of natural images has also been highlighted (Spehar et al., 2003; Graham and Field, 2007; Graham and Redies, 2010). Motivated by these claims and our previous findings that humans display a consistent preference across various images with fractal-like statistics, here we explore the possibility that observers' preference for visual patterns might be related to their sensitivity for such patterns. We measure sensitivity to simple visual patterns (sine-wave gratings varying in spatial frequency and random textures with varying scaling exponent) and find that they are highly correlated with visual preferences exhibited by the same observers. Although we do not attempt to offer a comprehensive neural model of aesthetic experience, we demonstrate a strong relationship between visual sensitivity and preference for simple visual patterns. Broadly speaking, our results support assertions that there is a close relationship between aesthetic experience and the sensory coding of natural stimuli.

No MeSH data available.