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With the growing recognition of the heterogeneity of major brain disorders, and particularly the schizophrenias (SZ), biomarkers are being sought that parse patient groups in ways that can be used to predict treatment response, prognosis, and pathophysiology. A primary focus to date has been to identify biomarkers that predict damage or dysfunction within brain systems in SZ patients, that could then serve as targets for interventions designed to "undo" the causative pathology. After almost 50 years as the predominant strategy for developing SZ therapeutics, evidence supporting the value of this "find what's broke and fix it" approach is lacking. Here, we suggest an alternative strategy of using biomarkers to identify evidence of spared neural and cognitive function in SZ patients, and matching these residual neural assets with therapies toward which they can be applied. We describe ways to extract and interpret evidence of "spared function," using neurocognitive, and neurophysiological measures, and, suggest that further evidence of available neuroplasticity might be gleaned from studies in which the response to drug challenges and "practice effects" are measured. Finally, we discuss examples in which "better" (more normal) performance in specific neurophysiological measures predict a positive response to a neurocognitive task or therapeutic intervention. We believe that our field stands to gain tremendous therapeutic leverage by focusing less on what is "wrong" with our patients, and instead, focusing more on what is "right".

Neurophysiological Biomarkers Informing the Clinical Neuroscience of Schizophrenia: Mismatch Negativity and Prepulse Inhibition of Startle