Investigating the Sense of Pleasure and Abstract Perception of Different Artistic Genres within Iranian culture

Document Type : Research Paper

Authors

1 Department of Psychology, Faculty of Psychology and Educational Science , University of Tehran, Tehran, Iran.

2 Department of Machine Intelligence and Robotics, Faculty of Electrical and Computer Engineering ,, college of engineering, University of Tehran, Tehran, Iran.

Abstract

The aim of this research was to investigate the subjective experience of visual delight and abstract perception in Iranian culture as it relates to a variety of artistic genres. Furthermore, the objective of the study was to create a uniform repository of visual stimuli that could be utilized in scientific inquiries, with a particular focus on providing assistance to art therapy practitioners. The experimental and cross-sectional investigation, which spanned the academic year 2021-2022, centred on students and graduates of the faculties of engineering and fine arts at Tehran University. Six participants (two males and four females) were selected as a cohort using an available sampling technique. Every participant evaluated a total of 1045 paintings spanning across five distinct artistic movements: Impressionism, Cubism, Color Fields, and Abstract. The assessment duties comprised assigning ratings to the paintings according to their aesthetic appeal and tangible qualities. Statistical measures including the mean, standard deviation, analysis of variance, and mixed linear regression analysis were utilized in the data analysis. Utilizing Python 3, in conjunction with statistical utilities such as scipy and pingouin, enabled the execution of the analysis. The results indicated that there were notable variations in liking ratings among different artistic forms, with the exception of abstract cubism and abstract color fields. On the contrary, substantial disparities were noted across all genres in the concreteness-rating task, except for color fields, abstract, and cubism, which exhibited no noteworthy differentiation from one another.

Keywords

References

Bar, M., & Neta, M. (2006). Humans prefer curved visual objects. Psychological Science, 17(8), 645–648. https://doi.org/10.1111/j.1467-9280.2006.01759.x
Barron, H. C., Dolan, R. J., & Behrens, T. E. J. (2013). Online evaluation of novel choices by simultaneous representation of multiple memories. Nature Neuroscience, 16(10), 1492–1498. https://doi.org/10.1038/nn.3515
Cela-Conde, C. J., Marty, G., Maestú, F., Ortiz, T., Munar, E., Fernández, A., Roca, M., Rosselló, J., & Quesney, F. (2004). Activation of the prefrontal cortex in the human visual aesthetic perception. Proceedings of the National Academy of Sciences of the United States of America, 101(16), 6321–6325. https://doi.org/10.1073/pnas.0401427101
Chatterjee, A., Widick, P., Sternschein, R., Smith, W., & Bromberger, B. (2010). The assessment of art attributes. Empirical Studies of the Arts, 28(2), 207–222. https://doi.org/10.2190/EM.28.2.f
Gantt, L. M., & Anderson, F. (2009). The Formal Elements Art Therapy Scale: A measurement system for global variables in art. Art therapy, 26(3), 124-129. https://doi.org/10.1080/07421656.2001.10129453
Goodman, D. (Ed.). (2008). The new rich in China: Future rulers, present lives (First edition). 2 Park Square. Milton Park. Abington Oxon OX14 RN. Routledge.
Iigaya, K., Yi, S., Wahle, I. A., Tanwisuth, K., & Doherty, J. P. O. (2021). A mixture of low- and high-level visual features. Nature Human Behaviour, 5(June). https://doi.org/10.1038/s41562-021-01124-6
Iigaya, K., Yi, S., Wahle, I. A., Tanwisuth, K., & O’Doherty, J. P. (2020). Aesthetic preference for art emerges from a weighted integration over hierarchically structured visual features in the brain. BioRxiv, 2020.02.09.940353. https://doi.org/10.1101/2020.02.09.940353
Kahnt, T., Heinzle, J., Park, S. Q., & Haynes, J. D. (2011). Decoding different roles for vmPFC and dlPFC in multi-attribute decision making. NeuroImage, 56(2), 709–715. https://doi.org/10.1016/j.neuroimage.2010.05.058
Leder, H., & Nadal, M. (2014). Ten years of a model of aesthetic appreciation and aesthetic judgments : The aesthetic episode – Developments and challenges in empirical aesthetics. 443–464. https://doi.org/10.1111/bjop.12084
Mallon, B., Redies, C., & Hayn-Leichsenring, G. U. (2014). Beauty in abstract paintings: Perceptual contrast and statistical properties. Frontiers in Human Neuroscience, 8(MAR), 1–14. https://doi.org/10.3389/fnhum.2014.00161
Ning, D. (1995). The science of art. Languages of Design, 3(1), 78–79. https://doi.org/10.1016/0927-3034(96)83741-4
Palmer, S. E., Schloss, K. B., & Sammartino, J. (2013). Visual aesthetics and human preference. Annual Review of Psychology, 64, 77–107. https://doi.org/10.1146/annurev-psych-120710-100504
Shimamura, A. P., & Palmer, S. E. (2012) Aesthetic Science: Connecting Minds, Brains, and Experience (2012), United Kingdom: Oxford University Press, USA. https://doi.org/10.1093/acprof:oso/9780199732142.001.0001
Slayton, S. C., D'Archer, J., & Kaplan, F. (2010). Outcome studies on the efficacy of art therapy: A review of findings. Art therapy, 27(3), 108-118. https://doi.org/10.1080/07421656.2010.10129660
Vaidya, A. R., Sefranek, M., & Fellows, L. K. (2018). Ventromedial Frontal Lobe Damage Alters how Specific Attributes are Weighed in Subjective Valuation. Cerebral Cortex, 28(11), 3857–3867. https://doi.org/10.1093/cercor/bhx246
Van Paasschen, J., Zamboni, E., Bacci, F., & Melcher, D. (2014). Consistent Emotions Elicited by Low-Level Visual Features in Abstract Art. Art and Perception, 2(1–2), 99–118. https://doi.org/10.1163/22134913-00002012
Wimmer, G. E., & Shohamy, D. (2012). Preference by association: How memory mechanisms in the hippocampus bias decisions. Science, 338(6104), 270–273. https://doi.org/10.1126/science.1223252
Journal of Applied Psychological Research
Volume 14, Issue 4
2024
Pages 335-347

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History

  • Receive Date: 15 December 2022
  • Revise Date: 09 January 2023
  • Accept Date: 17 February 2023
  • First Publish Date: 10 January 2024
  • Publish Date: 10 January 2024

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