Towards a network control theory of electroconvulsive therapy response

Abstract

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.

Formalizing psychological interventions through network control theory

“…Applied to Ecological Momentary Interventions (EMI), Fechtelpeter et al 27 showed that the results from network control theory can provide insightful information on putative mechanisms of change. Further, network control theory has been used to study the brain-behavior constructs ranging from studies in the clinical setting such as depression 28 , 29 , to cognitive concepts such as creativity 30 , and further to conceptual frameworks applied to psychological well-being 31 , clinical psychology 24 , and networked systems 9 , 32 .…”