Oscillatory traveling waves reveal predictive coding abnormalities in schizophrenia

Abstract

The computational mechanisms underlying psychiatric disorders are hotly debated. One hypothesis, grounded in the Bayesian predictive coding framework, proposes that schizophrenia patients have abnormalities in encoding prior beliefs about the environment, resulting in abnormal sensory inference, which can explain core aspects of the psychopathology, such as some of its symptoms. Here, we tested this hypothesis by identifying oscillatory traveling waves as neural signatures of predictive coding. By analyzing a EEG dataset. comprising 146 schizophrenia patients and 96 age-matched healthy controls, we found that schizophrenia patients have stronger top-down alpha-band traveling waves compared to healthy controls during resting state, reflecting stronger precise priors at higher levels of the predictive processing hierarchy. Conversely, we found stronger bottom-up alpha-band waves in schizophrenia patients during a visual task reflecting an alteration of lower sensory priors. Our results yield a novel spatial-based characterization of oscillatory dynamics in schizophrenia, considering brain rhythms as traveling waves and providing a unique framework to study the different components involved in a predictive coding scheme. Altogether, our findings significantly advance our understanding of the mechanisms involved in fundamental pathophysiological aspects of schizophrenia, promoting a more comprehensive and hypothesis-driven approach to psychiatric disorders. SignificanceWe provide novel evidence favoring the Bayesian predictive coding interpretation of schizophrenia. Relying on computational and experimental works that characterized electrophysiological correlates of predictive processes, we investigate oscillatory traveling waves in EEG data of 146 schizophrenia patients and 96 age-matched healthy controls. Our results reveal stronger top-down alpha-band traveling waves in schizophrenia patients, reflecting an increase in the precision of high-level priors. On the other hand, we observed an increase in bottom-up alpha-band waves during a visual task, in line with the proposed reduction in precision of low-level sensory priors. Our findings suggest that traveling waves analysis is a versatile technique to probe predictive processing mechanisms in different cognitive processes. Impairments in this mechanism may underlie perceptual alterations as well as the pronounced clinical symptoms of schizophrenia. The strong hypothesis-driven nature of our results accentuates the relevance of our findings.