An EEG-Based Neuroplastic Approach to Predictive Coding in People With Schizophrenia or Traumatic Brain Injury

Author:

Wynn Jonathan K.12ORCID,Green Michael F.12

Affiliation:

1. Center on Enhancement of Community Integration for Homeless Veterans, VA Greater Los Angeles Healthcare System, Los Angeles, CA, USA

2. Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA

Abstract

Despite different etiologies, people with schizophrenia (SCZ) or with traumatic brain injury (TBI) both show aberrant neuroplasticity. One neuroplastic mechanism that may be affected is prediction error coding. We used a roving mismatch negativity (rMMN) paradigm which uses different lengths of standard tone trains and is optimized to assess predictive coding. Twenty-five SCZ, 22 TBI (mild to moderate), and 25 healthy controls were assessed. We used a frequency-deviant rMMN in which the number of standards preceding the deviant was either 2, 6, or 36. We evaluated repetition positivity to the standard tone immediately preceding a deviant tone (repetition positivity [RP], to assess formation of the memory trace), deviant negativity to the deviant stimulus (deviant negativity [DN], which reflects signaling of a prediction error), and the difference wave between the 2 (the MMN). We found that SCZ showed reduced DN and MMN compared with healthy controls and with people with mild to moderate TBI. We did not detect impairments in any index (RP, DN, or MMN) in people with TBI compared to controls. Our findings suggest that prediction error coding assessed with rMMN is aberrant in SCZ but intact in TBI, though there is a suggestion that severity of head injury results in poorer prediction error coding.

Funder

U.S. Department of Veterans Affairs

Publisher

SAGE Publications

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