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. rsfMRI data were acquired from
healthy controls and from patients with remitted major depressive disorder on antidepressants.
Patients were assessed a second time either before or after discontinuation of the antidepressant,
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. 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. The seed-based analysis showed
that discontinuation resulted in an increased functional connectivity between the right dorsolateral
prefrontal cortex and the parietal cortex in non-relapsers. In an exploratory analysis, this functional
connectivity predicted relapse risk with a balanced accuracy of 0.86. Further seed-based analyses,
however, failed to reveal diferences in functional connectivity between patients and controls,
between relapsers and non-relapsers before discontinuation and changes due to discontinuation
independent of relapse. In conclusion, changes in the connectivity between the dorsolateral prefrontal
cortex and the posterior default mode network were associated with and predictive of relapse after
open-label antidepressant discontinuation. This fnding requires replication in a larger dataset