Computational Psychiatry & Decision-making

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  • doi pdf The relationship between resting-state functional connectivity, antidepressant discontinuation and depression relapse
  • Berwian IM, Wenzel J, Kuehn L, Schnuerer I, Kasper L, Veer IM, Seifritz E, Stephan KE, Walter H, Huys QJM
  • bioRxiv
  • Background: The risk of relapsing into depression after stopping antidepressants is high, but no established predictors exist. Resting-state functional magnetic resonance imaging (rsfMRI) measures may help predict relapse and identify the mechanisms by which relapses occur. Method: rsfMRI data were acquired from healthy controls and from patients with remitted major depressive disorder on antidepressants who were intent on discontinuing their medication. Patients went on to discontinue their antidepressants, were assessed a second time either before or after discontinuation and followed up for six months to assess relapse. A seed-based functional connectivity analysis was conducted focusing on the left subgenual anterior cingulate cortex and left posterior cingulate cortex. Seeds in the amygdala and dorsolateral prefrontal cortex were explored. Results: 44 healthy controls (age: 33.8 (10.5), 73% female) and 84 patients (age: 34.23 (10.8), 80% female) were included in the analysis. 29 patients went on to relapse and 38 remained well. Seed-based analysis failed to reveal differences in functional connectivity between patients and controls; and between relapsers and non-relapsers. Although overall there was no effect of antidepressant discontinuation, amongst non-relapsers discontinuation resulted in an increased functional connectivity between the right dorsolateral prefrontal cortex and the parietal cortex. Conclusion: No abnormalities in resting-state functional connectivity were detected in remitted patients on antidepressant medication. Resilience to relapse after open-label antidepressant discontinuation was associated with changes in the connectivity between the dorsolateral prefrontal cortex and the posterior default mode network.