Relationship Between Cortical Excitation and Inhibition and Task-Induced Activation and Deactivation: A Combined Magnetic Resonance Spectroscopy and Functional Magnetic Resonance Imaging Study at 7T in First-Episode Psychosis.

ABSTRACT

BACKGROUND: Schizophrenia is thought to be a disorder of brain dysconnectivity. An imbalance between cortical excitation/inhibition is also implicated, but the link between these abnormalities remains unclear. The present study used magnetic resonance spectroscopy and functional magnetic resonance imaging at 7T to investigate how measurements of glutamate and gamma-aminobutyric acid (GABA) relate to the blood oxygen level-dependent (BOLD) response during a cognitive task, and how these relationships are altered in schizophrenia. METHODS: Usable functional magnetic resonance imaging data from 17 first-episode psychosis (FEP) patients (4 women, 13 men) and 21 matched healthy control subjects (HCs) (5 women, 16 men) were acquired during a Stroop task. Within- and between-group comparisons of the BOLD response were performed. Neurometabolite levels were measured in the dorsal anterior cingulate cortex. Two multiple regressions investigated how glutamate, glutamine, and GABA related to the BOLD response in HCs and FEP patients separately. A third investigated between-group differences in the relationships between the BOLD response and each of these neurometabolites. RESULTS: Compared with HCs, FEP patients showed an increased BOLD response within regions of the executive and default mode networks. In FEP patients, the relationship between anterior cingulate cortex glutamate levels and the BOLD response in regions of the posterior default mode network was opposite to that of HCs. In FEP patients but not HCs, anterior cingulate cortex GABA levels correlated with the local BOLD response and with the Stroop reaction time. CONCLUSION: These results suggest a mechanism whereby alterations in the relationship between cortical glutamate/GABA and BOLD response is disrupting the dynamic of major neural networks, possibly affecting cognition.