Abstract
The mystery of aesthetics attracts scientists from various research fields. The topic of aesthetics, in combination with other disciplines such as neuroscience and computer science, has brought out the burgeoning fields of neuroaesthetics and computational aesthetics within less than two decades. Despite profound findings are carried out by experimental approaches in neuroaesthetics and by machine learning algorithms in computational neuroaesthetics, these two fields cannot be easily combined to benefit from each other and findings from each field are isolated. Computational neuroaesthetics, which inherits computational approaches from computational aesthetics and experimental approaches from neuroaesthetics, seems to be promising to bridge the gap between neuroaesthetics and computational aesthetics. Here, we review theoretical models and neuroimaging findings about brain activity in neuroaesthetics. Then machine learning algorithms and computational models in computational aesthetics are enumerated. Finally, we introduce studies in computational neuroaesthetics which combine computational models with neuroimaging data to analyze brain connectivity during aesthetic appreciation or give a prediction on aesthetic preference. This paper outlines the rich potential for computational neuroaesthetics to take advantages from both neuroaesthetics and computational aesthetics. We conclude by discussing some of the challenges and potential prospects in computational neuroaesthetics, and highlight issues for future consideration.
Highlights
Aesthetics, defined in the dictionary as “a set of principles concerned with the nature and appreciation of beauty” [1], plays a fundamental role in human’s history and culture
6 Conclusions In conclusion, as an emerging interdisciplinary research field, computational neuroaesthetics plays an important role to bridge findings of neural substrates from neuroaesthetics and computation algorithms from computational aesthetics. Taking advantage from both methodological advances in computational aesthetics and theoretical advances in neuroaesthetics, computational neuroaesthetics can learn much from these two fields and gain increased momentum
We have seen that a series of recent works have ventured to study aesthetic appreciation from the point of machine learning and functional brain networks
Summary
Aesthetics, defined in the dictionary as “a set of principles concerned with the nature and appreciation of beauty” [1], plays a fundamental role in human’s history and culture. With the advance of technology, modern neuroimaging tools, such as electroencephalogram (EEG), magnetoencephalogram (MEG), and functional magnetic resonance imaging (fMRI), have become available for researchers The application of these neuroimaging techniques in experimental aesthetics and the goal to understand neurobiological basis of our cognitive process during aesthetic experience have blossomed into a newly research perspective called neuroaesthetics [9]. Studies in computational aesthetics can be the test bed for aesthetic measurements and stretch our understanding on visual attributes that affect aesthetic appreciation and art generation. Computational neuroaesthetics, still in its infancy, seems to be promising to assemble the pieces of puzzle from neuroaesthetics and computational aesthetics It has emerged from three research fields including aesthetics, neuroscience, and computer science. Studies measuring brain information flows during aesthetic appreciation and developing computational models based on neural activities to make aesthetic evaluation predictions should be central to computational neuroaesthetics. Topics include theoretical models and neural underpinning of aesthetic appreciation from neuroaesthetics, automatic image quality assessment by computers from computational aesthetics, and computational models for measuring and modeling brain activities in computational neuroaesthetics
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
