Towards Computational Cognitive Modeling of Mental Imagery The Attention-Based Quantification Theory

Mental imagery is the human ability to imagine and reason with visuo-spatial information. It is crucial for everyday tasks such as describing a route or remembering the form of objects. The so-called imagery debate has been centered around the question how mental imagery is realized, i.e., what structures and algorithms can plausibly explain and model mental imagery. There is, however, little progress on a coherent theory that can sufficiently cover the diversity of the empirical data. This article presents a new theory of mental imagery, which in contrast to other contemporary theories is formalized as a computational cognitive model. We will compare this theory to the contemporary theories using two representative phenomena of mental imagery. We will argue that formalized theories can advance the currently stagnant imagery debate.