Figure 1.
Study design and analysis pipeline. We initially synthesized published literature to identify the locations of longitudinal brain functional alterations (increase and decrease separately) induced by ketamine treatment in depressed patients. By integrating these affected brain locations with large-scale resting-state fMRI datasets (the HV and MDD datasets), we then leveraged the FCNM approach to construct ketamine-induced brain functional alteration networks (hyper-functional and hypo-functional networks respectively). Specifically, spheres centered at each coordinate of a contrast were firstly created and merged together to yield a contrast-specific combined seed mask. Second, in combination with the resting-state fMRI data, we calculated a contrast seed-to-whole brain rsFC map for each subject. Third, the subject-level rsFC maps were entered into a voxel-wise one-sample t test to identify brain areas functionally connected to each contrast seed. Fourth, the resultant group-level t maps were thresholded and binarized. Finally, the binarized maps were overlaid to produce 2 network probability maps, which were thresholded at 50% to yield ketamine-induced hyper-functional and hypo-functional networks respectively. Abbreviations: HV, healthy volunteer; MDD, major depressive disorder; rs-fMRI, resting-state functional magnetic resonance imaging; rsFC, resting-state functional connectivity.