Evolution of Neuroaesthetic Variables in Portrait Paintings Throughout the Renaissance To compose art, artists rely on a set of sensory evaluations performed fluently by the brain. The outcome of these evaluations, which we call neuroaesthetic variables, helps to compose art with high aesthetic value. In this study, we probed whether these variables varied across art periods despite relatively unvaried neural function. We measured several neuroaesthetic variables in portrait paintings from the Early and High Renaissance, and from Mannerism. The variables included symmetry, balance, and contrast (chiaroscuro), as well as intensity and spatial complexities measured by two forms of normalized entropy. The results showed that the degree of symmetry remained relatively constant during the Renaissance. However, the balance of portraits decayed abruptly at the end of the Early Renaissance, that is, at the closing of the 15th century. Intensity and spatial complexities, and thus entropies, of portraits also fell in such manner around the same time. Our data also showed that the decline of complexity and entropy could be attributed to the rise of chiaroscuro. With few exceptions, the values of aesthetic variables from the top of artists of the Renaissance resembled those of their peers. We conclude that neuroaesthetic variables have flexibility to change in brains of artists (and observers).

Machine, Discourse and Power: From Machine Learning in Construction of 3D Face to Art and Creativity. The 3D face reconstruction based on a single image can be done recently by training the machine to learn from the database. The performance and accuracy of 3D facial structure and the geometry have largely improved with the powerful calculation of machine and its expanding data. The 3D face reconstruction can be applied in both still images and moving images and recently such technology draws attention in the art field such as portrait representation, facial recognition, surveillance art, etc. By using artificial intelligence (AI) technology and machine learning, artists are able to create artwork with hybridity characteristic, which consists of both human perspective, and machine creativity, which opens up a new gateway to the art world. The capability of artists in creating artwork, particularly portrait art in this research, has been enhanced in terms of technological and theoretical perspective. Artists can represent faces and understand 3D geometry in new ways by breaking through the traditional limitation; it also provides alternative methods in facial visualization beyond the expectation. Traditional expression and technique can be expended to a new dimension; the technology helps artists to think out of the box and continue to create new movement and ism throughout the art history. Moreover, the traditional belief about the importance of the originality of artistsxe2x80x99 mind, sense, perspective and techniques in creating artwork can now be redefined by machine and artificial intelligence. A new form in art and creativity, and even knowledge and history has been developed. This paper attempts to discuss the essential transformation in dimensional imagery and its aesthetic experiences through machine learning means, and the shift of discourse of power from human to machine.