Pareidolia Without Error: A Structural Account

This paper proposes a non-reductive structural alignment between pareidolic experience and contemporary models of human perception, particularly within frameworks of predictive processing. Rather than treating pareidolia as a perceptual error or cognitive malfunction, it is argued that pareidolic phenomena arise naturally from highly sensitive perceptual systems operating under conditions of uncertainty. By presenting a sequence of experiential states and aligning them with established neuroscientific mechanisms, the paper demonstrates that pareidolia can be understood as a lawful outcome of perceptual prediction and attribution, without reducing lived experience to neural causation.