The narrative self-model in schizophrenia: integrating predictive processing with phenomenological psychopathology

Over the last several years, predictive processing approaches to computational neuropsychiatry have been gaining explanatory traction. According to these accounts, some of the positive symptoms of schizophrenia arise from aberrant precision-weighting during hierarchical Bayesian inference. In contrast to computational approaches, the phenomenological tradition in psychiatry holds that disruptions or alterations of the self (Ichst & ouml;rungen) lie at the core of schizophrenia. In this article, we aim to integrate these approaches. We align ourselves with the phenomenological insight that self-disturbances lie at the core of schizophrenia and with the hierarchical conception of the self-model that emerges from the predictive processing architecture. We suggest that disruptions of the "hard core" of the narrative self-model might be partially involved in the generation of aberrant experiences and hyperreflexivity, and in some aspects of the sense of self-alienation and ambiguity that is characteristic of the phenomenology of schizophrenia.