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An emerging body of work in cognitive philosophy and computational neuroscience depicts human brains as prediction machines – multi-level networks that specialize in using generative models to both match and anticipate the evolving stream of sensory information. However, the relationship between these posited cascades of prediction and conscious human experience itself remains unclear. Recent work in computational psychiatry provides important clues. For example, it is thought that malfunctions in hierarchical inference can explain core patterns of alteration seen in autism and schizophrenia, and can shed new light on so-called ‘psychogenic’ symptoms - functional impairments without standard organic causes. Such accounts reveal the deep continuities between perception and hallucination and may help reveal common processing motifs underlying both typical and atypical forms of human experience.VIDEO LINK