  With the increased sophistication of AI techniques, the application of these
systems has been expanding to ever newer fields. Increasingly, these systems
are being used in modeling of human aesthetics and creativity, e.g. how humans
create artworks and design products. Our lab has developed one such AI
creativity deep learning system that can be used to create artworks in the form
of images and videos. In this paper, we describe this system and its use in
studying the human visual system and the formation of aesthetic experiences.
Specifically, we show how time-based AI created media can be used to explore
the nature of the dual-pathway neuro-architecture of the human visual system
and how this relates to higher cognitive judgments such as aesthetic
experiences that rely on these divergent information streams. We propose a
theoretical framework for how the movement within percepts such as video clips,
causes the engagement of reflexive attention and a subsequent focus on visual
information that are primarily processed via the dorsal stream, thereby
modulating aesthetic experiences that rely on information relayed via the
ventral stream. We outline our recent study in support of our proposed
framework, which serves as the first study that investigates the relationship
between the two visual streams and aesthetic experiences.
