Schizophrenia is a debilitating condition that affects both patients and society at large. Early identification of those at “clinical high risk” (CHR) for developing the disorder is crucial for timely intervention. While some clinical variables can predict outcomes in these high-risk patients, there is a need for more reliable predictors to guide treatment. This is especially important given the wide range of outcomes among those at CHR, some of whom may recover well while others continue to experience severe symptoms and functional impairments.
Our project has two main objectives. The first is to validate the use of electroencephalographic event-related potentials (ERPs), specifically the mismatch negativity (MMN) and the N400 semantic priming effect, as reliable predictors of outcomes in individuals at CHR for psychosis. These ERPs are measures of brain activity related to auditory processing and semantic memory, respectively, and have been found to be altered in individuals with schizophrenia and those at high risk. The second aim is to use these ERP measures to better understand the underlying brain mechanisms that contribute to the risk of developing psychosis.
