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Anterior insular cortex glutamate-glutamine (Glx) levels predict general psychopathology via heightened error
Haeorum Park1, Minchul Kim1,2, Jaejoong Kim1,3
1Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.
Introduction:
The anterior insular cortex (AIC) integrates interoceptive, cognitive-emotional, and error-monitoring signals, and is consistently hyperactive in anxiety and depression. Converging evidence links elevated glutamate + glutamine (Glx) in fronto-insular regions to stress reactivity; however, it is unknown whether AIC Glx relates to a transdiagnostic general psychopathology factor (G-score) or to the tendency to overweight prediction errors during learning. We therefore combined functional MRS (fMRS) with reinforcement-learning modeling to test whether (i) baseline AIC Glx predicts the G-score derived from bifactor analysis of PHQ-9, GAD-7, and STAI-X1, and (ii) task-evoked Glx changes track individual differences in error sensitivity during gain- and loss-based learning.
Methods:
Fifty-six healthy adults (22 ± 2 yr, 16 women) completed the questionnaires and performed a two-armed bandit task (40 loss then 40 gain trials) while single-voxel semi-LASER spectra were acquired from AIC and medial prefrontal cortex (mPFC) at rest and during each block. Six Rescorla-Wagner variants were fitted to the choices; the best model (based on the lowest LOOIC) included error sensitivity, decision temperature, and value decay. Glx (CRLB < 20%) was quantified using LCModel and analyzed with repeated-measures ANOVA and Bonferroni-corrected correlations; mediation was assessed using Baron-Kenny steps (α = 0.05).
Results:
Baseline AIC Glx correlated with the G-score (r = 0.39, p = 0.004) and with error sensitivity for gains and losses (r≈0.41-0.44, p ≤ 0.005); mPFC Glx showed no such relations. AIC Glx fell during gain learning (-2.21%, p = 0.034) and remained low post-task, whereas mPFC Glx was unchanged. Error sensitivity fully mediated the AIC-Glx/G-score link; associations were specific to Glx, not other metabolites.
Discussion:
Higher excitatory tone in the AIC appears to enlarge prediction-error weighting, which in turn amplifies a shared anxiety-depression dimension. Dynamic Glx reductions during reward learning suggest acute metabolic demand superimposed on a trait-like baseline that biaes cognition. Targeting insular glutamatergic function-pharmacologically or via neuromodulation-may therefore mitigate maladaptive error processing that underlies internalizing psychopathology.
