Oscillatory traveling waves reveal predictive coding abnormalities in schizophrenia

Author:

Alamia Andrea,Gordillo DarioORCID,Chkonia Eka,Roinishvili Maya,Cappe Celine,Herzog Michael H.

Abstract

AbstractIn recent years, increasing interest has been in describing the computational mechanisms underlying psychiatric disorders. Diverse hypotheses aim at characterizing cognitive and perceptual alterations in schizophrenia and its major symptoms. One hypothesis, grounded in the Bayesian predictive coding framework, proposes that schizophrenia patients have alterations in encoding prior beliefs about the environment, resulting in abnormal sensory inference that may underlie some core aspects of this psychopathology. Here, we test this hypothesis from a neurophysiological perspective, leveraging recent work identifying oscillatory traveling waves as neural signatures of predictive coding. By analyzing one of the largest EEG datasets, 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, thereby reflecting an increased flow of prior information from higher-level into sensory brain areas. EEG traveling waves during resting state were strongly correlated to those observed during a visual backward masking task, showing that schizophrenia patients have an inherent impairment in the flow of prior signals into sensory areas that spans many functioning domains. Importantly, the present 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. Taking advantage of computational and experimental works that characterized the electrophysiological correlates of predictive processes, we investigate the pattern of oscillatory traveling waves in a large EEG dataset 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 alteration in the precision of their high-level priors.Traveling waves observed during resting-state were strongly correlated to those observed during a visual backward masking task, suggesting that traveling waves probe a general mechanism of predictive processing. Impairments in this mechanism may underlie some of the major perceptual and cognitive alterations as well as the pronounced clinical symptoms of schizophrenia. The strong hypothesis-driven nature of our results accentuates the relevance of our findings.

Publisher

Cold Spring Harbor Laboratory

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