Schizophrenia research under the framework of predictive coding: body, language, and others

TL;DR

This paper reviews predictive coding models related to schizophrenia, emphasizing the need for a model-oriented approach to develop effective therapies by understanding embodiment, language, social interaction, and subjective experience.

Contribution

It provides a comprehensive summary of predictive coding models in schizophrenia and advocates for a therapy-oriented research direction within this framework.

Findings

Predictive coding models explain various schizophrenia symptoms.

Impairments in embodiment, language, and social cognition are linked to predictive coding deficits.

The paper suggests integrating these models to advance therapeutic strategies.

Abstract

Although there have been so many studies on schizophrenia under the framework of predictive coding, works focusing on treatment are very preliminary. A model-oriented, operationalist, and comprehensive understanding of schizophrenia would promote the therapy turn of further research. We summarize predictive coding models of embodiment, co-occurrence of over- and under-weighting priors, subjective time processing, language production or comprehension, self-or-other inference, and social interaction. Corresponding impairments and clinical manifestations of schizophrenia are reviewed under these models at the same time. Finally, we discuss why and how to inaugurate a therapy turn of further research under the framework of predictive coding.