Dynamic causal modelling of resting-state fMRI to predict ketamine response in MDD

ETH Translational Neuromodeling Unit (spring 2025), Prof. Klaas Enno Stephan: test whether baseline resting-state fMRI predicts response to a single ketamine infusion in major depressive disorder (NIMH open data; after QC, n=26). Spectral DCMs at 4 / 11 / 15 nodes (21-node too costly); A-matrices feed logistic regression and related models for binary/multi-class response and MADRS regression. Best: 4-node DMN + logistic regression (about 73% accuracy, F1 0.71, macro-recall 0.82); larger DCMs near 65%. Finer stratification and continuous outcomes weak on this cohort—parsimony beats complexity; future validation and clinical covariates.