Neuroesthetics

Neuroaesthetics (or neuroaesthetics) is a sub-discipline of applied aesthetics. Empirical aesthetics takes a scientific approach to the study of aesthetic experience of art, music, or any object that can give rise to aesthetic judgments. Neuroesthetics is a term coined by Semir Zeki in 1999 and received its formal definition in 2002 as the scientific study of the neural bases for the contemplation and creation of a work of art. Anthropologists and evolutionary biologists alike have accumulated evidence suggesting that human interest in, and creation of, art evolved as an evolutionarily necessary mechanism for survival across cultures and throughout history. Neuroesthetics uses neuroscience to explain and understand the aesthetic experiences at the neurological level. The topic attracts scholars from many disciplines including neuroscientists, art historians, artists, art therapists and psychologists.

Overview Neuroaesthetics is a field of experimental science that aims to combine Neuroscience (Neuro-Psychology) research with aesthetics by investigating the "perception, production, and response to art, as well as interactions with objects and scenes that evoke an intense feeling, often of pleasure." The recently developed field seeks, among other things, the neural correlates of aesthetic judgment and creativity, and how these help humans communicate and connect. It is argued that visual aesthetics, namely the capacity of assigning different degrees of beauty to certain forms, colors, or movements, is a human trait acquired after the divergence of human and other ape lineages, rendering the experience of beauty a defining characteristic of humankind. One core question for the field is whether art or aesthetic preferences are guided by a set of scientific laws or principles. Additionally, the evolutionary rationale for the formation and characteristics of these principles are sought. It is believed that identification of the brain circuitry involved in aesthetic judgments (e.g., by using through the use of brain imaging) can help pinpoint the origin of these responses. Many scholars, including neuroscientists, remain skeptical of the reductive approach adopted by neuroaesthetics. The subfield of Computational Neuroaesthetics has aimed to utilize machine learning algorithms in conjunction with neuroimaging data to predict what humans would find most aesthetically pleasing. This field was pioneered by Fechner and Birkhoff in 1933; however it was years later that technology caught up enough to test, and prove, their hypotheses that aesthetics could be measured in a mathematical way. Real world applications of these models include recommending products via online advertisement. However, modeling serves the broader purpose of building scientific understanding and understanding the mechanisms guiding decision making and other cognitive processes by simulating the involved neural architecture.

… excerpt ends here. Continue reading the full article.