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Jacek Rogala,  Beata Bajno,  Andrzej Wróbel

A hidden message: Decoding artistic intent

PsyCh Journal Institute of Psychology,  Chinese Academy of Sciences    
First published:  13 July 2020


Understanding how art makes impressions upon the perceiver has been
a fundamental topic of philosophical interest since the time of ancient Greece. However, the extent of artistic perception and aesthetic appreciation has been
the topic of empirical studies only recently, following the emergence of psychology as an independent field of science. The present study discusses the hypothesis that the impression created by artwork on the viewer can be predicted by examining activity of neuronal networks. In particular, we focus on neural activity evoked by abstract stimuli that matches elements of the viewers' previously learned conceptual dictionary. We show that artistic appreciation fundamentally depends on how easily the author's intent expressed in his or her artwork can be abstracted and decoded, on a neuronal level, into new or merged concept networks. More diverse intellectual and personal experiences - and their corollary neural networks - may facilitate the creation of new networks. These new networks, in turn, modulate the extent to which art can be apprehended and appreciated.

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Dr Jacek Rogala  -  Bioimaging Research Center, World Hearing Center,
Institute of Physiology and Pathology of H

Mgr inż. arch. Beata Bajno  -  Independent artist

Prof. dr hab. Andrzej Wróbel  -  Department of Epistemology, Institute of Philosophy,
University of Warsaw

When we look at a painting, what is it that we observe? What catches our attention, and why? Do we look for hidden messages in paintings? Is it easy to create a visually intriguing image without being an artist? These are some of the questions we tried to address by carrying out a psychological and neurophysiological experiment, using both human-painted images and images generated by
an artificial neural network.
The primary goal of the experiment was to measure people’s physiological and psychological reactions to abstract images created by an artist and those
generated by a neural network, and to check if those reactions differ. We stipulated at the outset that our goal was not to produce “artificial paintings” perfectly
imitating “real” art, or to improve methods of doing so (although this might be possible by cleverly applying our findings). Moreover, the imperfect nature of the
generated images allowed us to draw interesting conclusions and attempt to answer some of the questions mentioned above.


We thank the artist, Ms. Lidia Kot, and Prof. Romuald Janik for providing the artworks we used in our study: original paintings and appropriately selected images
produced by BigGAN.

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Prof. Marek Kuś   works at the PAS Centerfor Theoretical Physicsin Warsaw. He is a member of the Center for Systemic Risk Research at the University of Warsaw. His main areas of scientific work are mathematical physics, quantum computing, and the application of mathematical methods in social and humansciences

Jacek Rogala, PhD   is educated as a biologist specializing in cognitive processes.
He initially worked at the Nencki Institute of Experimental Biology and then at the Faculty
of Physics, University of Warsaw. Currently at the Center for Research on Culture, Language, and Mind at the University of Warsaw, where he focuses on the perception of art.

Joanna Dreszer, PhD   works as an Assistant Professor at the Institute of Psychology, Nicolaus
Copernicus University in Toruń. She studies the neuropsychological correlates of aesthetic

experience, particularly focusing on the state of flow and changes in time perception.

Beata Bajno, M.Arch.E.   is a visual artist and architect. She co-initiated a research project at the Center for Systemic Risk Research at the University of Warsaw, dedicated to the impact of art. She is interested in exploring how personal world models develop dynamically. She creates immersive light installations, graphics, and photographs.

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