RT Journal Article SR Electronic T1 1/f neural noise is a better predictor of schizophrenia than neural oscillations JF bioRxiv FD Cold Spring Harbor Laboratory SP 113449 DO 10.1101/113449 A1 Erik J. Peterson A1 Burke Q. Rosen A1 Alana M. Campbell A1 Aysenil Belger A1 Bradley Voytek YR 2017 UL http://biorxiv.org/content/early/2017/03/08/113449.abstract AB Schizophrenia has been associated with separate irregularities in several neural oscillatory frequency bands, including theta, alpha, and gamma. Our multivariate classification suggests that instead of irregularities in many frequency bands, schizophrenia-related EEG differences may better be explained by an overall shift in neural noise, reflected by a change in the 1/f slope of the power spectrum.Significance statement Understanding the neurobiological origins of schizophrenia, and identifying reliable biomarkers, are both of critical importance in improving treatment of that disease. While we lack predictive biomarkers, numerous studies have observed disruptions to neural oscillations in schizophrenia patients. This literature has, in part, lead to schizophrenia being characterized as disease of disrupted neural coordination. We report however that changes to background noise (i.e., 1/f noise) are a substantially better predictor of schizophrenia than oscillatory power. The observed alterations in neural noise are consistent with inhibitory neuron dysfunctions associated with schizophrenia, allowing for a direct link between noninvasive EEG and neurobiological deficits.