Investigation of influence of loss function weights of cycle-consistent adversarial networks on generation of pareidolia stimuli

Abstract

Pareidolia is the psychological tendency of perceiving non-facial objects as faces. The pareidolia test utilizes this tendency for diagnosis, to identify patients suffering from Lewy body dementia. A typical symptom of Lewy body dementia consists of visual-hallucination of non-existing individuals, which can be created artificially by pareidolia stimuli. No research has been conducted on how dementia progression relates to the pareidolia test, primarily because it is difficult to systematically generate test stimuli with different strengths of pareidolia-inducing power. To overcome this difficulty, we utilize the cycle-consistent adversarial networks (CycleGAN). Two loss functions are associated with CycleGAN. In this paper, the influence of the weight of one of the CycleGAN loss functions, the “cycle consistency loss”, is investigated. The results demonstrate that, as expected, there are systematic differences in inducing pareidolia like facial perception.