Towards a Unifying Cognitive, Neurophysiological, and Computational Neuroscience Account of Schizophrenia

Author:

Heinz Andreas1,Murray Graham K2,Schlagenhauf Florian13,Sterzer Philipp1,Grace Anthony A456,Waltz James A7ORCID

Affiliation:

1. Department of Psychiatry and Psychotherapy, Charité Campus Mitte, Charité—Universitätsmedizin Berlin, Berlin, Germany

2. Department of Psychiatry, University of Cambridge, Cambridgeshire, UK

3. Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany

4. Department of Neuroscience, University of Pittsburgh, Pittsburgh, PA

5. Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA

6. Department of Psychology, University of Pittsburgh, Pittsburgh, PA

7. Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD

Abstract

Abstract Psychotic experiences may be understood as altered information processing due to aberrant neural computations. A prominent example of such neural computations is the computation of prediction errors (PEs), which signal the difference between expected and experienced events. Among other areas showing PE coding, hippocampal-prefrontal-striatal neurocircuits play a prominent role in information processing. Dysregulation of dopaminergic signaling, often secondary to psychosocial stress, is thought to interfere with the processing of biologically important events (such as reward prediction errors) and result in the aberrant attribution of salience to irrelevant sensory stimuli and internal representations. Bayesian hierarchical predictive coding offers a promising framework for the identification of dysfunctional neurocomputational processes and the development of a mechanistic understanding of psychotic experience. According to this framework, mismatches between prior beliefs encoded at higher levels of the cortical hierarchy and lower-level (sensory) information can also be thought of as PEs, with important consequences for belief updating. Low levels of precision in the representation of prior beliefs relative to sensory data, as well as dysfunctional interactions between prior beliefs and sensory data in an ever-changing environment, have been suggested as a general mechanism underlying psychotic experiences. Translating the promise of the Bayesian hierarchical predictive coding into patient benefit will come from integrating this framework with existing knowledge of the etiology and pathophysiology of psychosis, especially regarding hippocampal-prefrontal-striatal network function and neural mechanisms of information processing and belief updating.

Funder

German Research Foundation

National Institutes of Health

Publisher

Oxford University Press (OUP)

Subject

Psychiatry and Mental health

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