Two-State Effective Connectivity Predicts the effect of Anterior Cingulate Cortex Excitatory / Inhibitory Balance on Posterior Cingulate Cortex

Abstract

Aims Excitatory/inhibitory imbalance - the equilibrium between glutamatergic excitation and {gamma}-Aminobutyric acid (GABA)ergic inhibition - is implicated in psychosis and may precede psychosis onset. Methods To investigate whether excitatory/inhibitory balance relates to subclinical psychotic experiences, anxiety and depression, we developed a network-level measure integrating Magnetic Resonance Spectroscopy Glutamate/GABA ratios with effective connectivity during resting-state fMRI. In 20 healthy young adults (aged between 18-32; 50% female), we first measured excitatory/inhibitory balance, operationalised as Glutamate/GABA and Glutamate+Glutamine(Glx)/GABA ratio, in the dorsal anterior cingulate cortex. Second, we applied Two-state Dynamic Causal Modelling to assess effective connectivity of the default-mode network, using these ratios as empirical priors to determine how they translate into network connectivity. Third, we ran Bayesian Model Selection at the model and family levels to identify the optimal models. Results The two-state model with Glx/GABA ratio as direct input into the posterior cingulate cortex best explained the data. This best-fitting model incorporated the neurometabolite ratio with Glutamate and GABA and used two-state connectivity. Conclusions Excitatory/inhibitory balance underlies resting-state effective connectivity, with the Glx/GABA ratio shaping connectivity networks. This pathway highlights excitatory/inhibitory balance as a predictor of two-state brain networks, potentially aiding identification of high-risk individuals and informing new interventions.