PT  - JOURNAL ARTICLE
AU  - Erik J. Peterson
AU  - Burke Q. Rosen
AU  - Alana M. Campbell
AU  - Aysenil Belger
AU  - Bradley Voytek
TI  - 1/<em>f</em> neural noise is a better predictor of schizophrenia than neural oscillations
AID  - 10.1101/113449
DP  - 2018 Jan 01
TA  - bioRxiv
PG  - 113449
4099  - http://biorxiv.org/content/early/2018/06/27/113449.short
4100  - http://biorxiv.org/content/early/2018/06/27/113449.full
AB  - Schizophrenia has been associated with separate irregularities in several neural oscillatory frequency bands, including theta, alpha, and gamma. Our multivariate classification of human EEG suggests that instead of irregularities in many frequency bands, schizophrenia-related electrophysiological 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 both oscillatory power and participants own behavioral performance. 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.None