Only one third of individuals identified as being at clinical high risk for psychosis actually convert to a psychotic disorder within a 3 year follow-up period. This risk assessment is based on the presence of sub-threshold psychotic-like symptoms.
Thus, clinical symptom criteria alone do not predict future psychosis risk with sufficient accuracy to justify aggressive early intervention, especially with medications such as antipsychotics that produce significant side effects.
Accordingly, there is a strong imperative to develop biomarkers of psychosis risk that can improve the ability to predict which individuals are most likely to transition to a psychotic disorder.
A study published in the current issue of Biological Psychiatry provides evidence that mismatch negativity (MMN), an event-related brain potential component derived from scalp electroencephalography (EEG) recordings, may be such a biomarker.
Mismatch negativity is an EEG signal that is elicited automatically from auditory cortex and frontal lobe regions of the brain in response to sounds that deviate from preceding sounds in pitch, duration, or other auditory features, even when one is not paying attention to the sounds. This electrophysiological measure of auditory deviance detection is thought to reflect short term plasticity in the brain, since it depends on the formation of a short term memory of recently heard sounds in order to detect a deviant sound.
Mismatch negativity is known to be reduced in patients with full-blown schizophrenia.
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