In early-phase psychosis, EIS are superior to TAU across all meta-analyzable outcomes. These results support the need for funding and use of EIS in patients with early-phase psychosis.

Introduction Only about one third of patients at high risk for psychosis based on current clinical criteria convert to a psychotic disorder within a 2.5-year follow-up period. Targeting clinical high-risk (CHR) individuals for preventive interventions could expose many to unnecessary treatments, underscoring the need to enhance predictive accuracy with non-clinical measures. Candidate measures include event-related potential (ERP) components with established sensitivity to schizophrenia. Here we examined the mismatch negativity (MMN) component of the ERP elicited automatically by auditory deviance in CHR and early illness schizophrenia (ESZ) patients. We also examined whether MMN predicted subsequent conversion to psychosis in CHR patients. Method MMN to auditory deviants (duration, frequency, and duration+frequency “double deviant”) were assessed in 44 healthy controls (HC), 19 ESZ, and 38 CHR patients. Within CHR patients, 15 converters to psychosis were compared to 16 non-converters with at least 12 months of clinical follow-up. Hierarchical Cox regression examined the ability of MMN to predict time to psychosis onset in CHR patients. Results Irrespective of deviant type, MMN was significantly reduced in ESZ and CHR patients relative to HC, and in CHR converters relative to non-converters. MMN did not significantly differentiate ESZ and CHR patients. The duration+frequency double deviant MMN, but not the single deviant MMNs, significantly predicted the time to psychosis onset in CHR patients. Conclusions Neurophysiological mechanisms underlying automatic processing of auditory deviance, as reflected by the duration+frequency double deviant MMN, are compromised prior to psychosis onset, and can enhance the prediction of psychosis risk among CHR patients.

Recent theoretical accounts have proposed excitation (E) and inhibition (I) imbalance as a possible mechanistic, network-level hypothesis underlying neural and behavioral dysfunction across neurodevelopmental disorders, particularly autism spectrum disorder (ASD) and schizophrenia (SCZ). These two disorders share some overlap in their clinical presentation as well as convergence in their underlying genes and neurobiology. However, there are also clear points of dissociation in terms of phenotypes and putatively affected neural circuitry. Here we highlight emerging work from the clinical neuroscience literature examining neural correlates of E/I imbalance across children and adults with ASD and adults with both chronic and early-course SCZ. We discuss findings from diverse neuroimaging studies across distinct modalities, conducted with EEG, MEG, 1H-MRS, and fMRI, including effects observed both during task and at rest. Throughout this review we discuss points of convergence and divergence in the ASD and SCZ literature, with a focus on disruptions in neural E/I balance. We also consider these findings in relation to predictions generated by theoretical neuroscience, particularly computational models predicting E/I imbalance across disorders. Finally, we discuss how human non-invasive neuroimaging can benefit from pharmacological challenge studies to reveal mechanisms in ASD and SCZ. Collectively, we attempt to shed light on shared and divergent neuroimaging effects across disorders with the goal of informing future research examining the mechanisms underlying the E/I imbalance hypothesis across neurodevelopmental disorders. We posit that such translational efforts are vital to facilitate development of neurobiologically informed treatment strategies across neuropsychiatric conditions.

Brain levels of glucose and lactate in the extracellular fluid (ECF), which reflects the environment to which neurons are exposed, have never been studied in humans under conditions of varying glycemia. The authors used intracerebral microdialysis in conscious human subjects undergoing electrophysiologic evaluation for medically intractable epilepsy and measured ECF levels of glucose and lactate under basal conditions and during a hyperglycemia-hypoglycemia clamp study. Only measurements from nonepileptogenic areas were included. Under basal conditions, the authors found the metabolic milieu in the brain to be strikingly different from that in the circulation. In contrast to plasma, lactate levels in brain ECF were threefold higher than glucose. Results from complementary studies in rats were consistent with the human data. During the hyperglycemia-hypoglycemia clamp study the relationship between plasma and brain ECF levels of glucose remained similar, but changes in brain ECF glucose lagged approximately 30 minutes behind changes in plasma. The data demonstrate that the brain is exposed to substantially lower levels of glucose and higher levels of lactate than those in plasma; moreover, the brain appears to be a site of significant anaerobic glycolysis, raising the possibility that glucose-derived lactate is an important fuel for the brain.