In PNAS nexus
Electroconvulsive Therapy (ECT) is arguably the most effective intervention for treatment-resistant depression. While large interindividual variability exists, a theory capable of explaining individual response to ECT remains elusive. To address this, we posit a quantitative, mechanistic framework of ECT response based on Network Control Theory (NCT). Then, we empirically test our approach and employ it to predict ECT treatment response. To this end, we derive a formal association between Postictal Suppression Index (PSI)-an ECT seizure quality index-and whole-brain modal and average controllability, NCT metrics based on white-matter brain network architecture, respectively. Exploiting the known association of ECT response and PSI, we then hypothesized an association between our controllability metrics and ECT response mediated by PSI. We formally tested this conjecture in N = 50 depressive patients undergoing ECT. We show that whole-brain controllability metrics based on pre-ECT structural connectome data predict ECT response in accordance with our hypotheses. In addition, we show the expected mediation effects via PSI. Importantly, our theoretically motivated metrics are at least on par with extensive machine learning models based on pre-ECT connectome data. In summary, we derived and tested a control-theoretic framework capable of predicting ECT response based on individual brain network architecture. It makes testable, quantitative predictions regarding individual therapeutic response, which are corroborated by strong empirical evidence. Our work might constitute a starting point for a comprehensive, quantitative theory of personalized ECT interventions rooted in control theory.
Hahn Tim, Jamalabadi Hamidreza, Nozari Erfan, Winter Nils R, Ernsting Jan, Gruber Marius, Mauritz Marco J, Grumbach Pascal, Fisch Lukas, Leenings Ramona, Sarink Kelvin, Blanke Julian, Vennekate Leon Kleine, Emden Daniel, Opel Nils, Grotegerd Dominik, Enneking Verena, Meinert Susanne, Borgers Tiana, Klug Melissa, Leehr Elisabeth J, Dohm Katharina, Heindel Walter, Gross Joachim, Dannlowski Udo, Redlich Ronny, Repple Jonathan
2023-Feb
diffusion tensor imaging, electroconvulsive therapy, major depressive disorder, network control theory, postictal suppression index
