Network fingerprints to distinguish bipolar and unipolar depression by fMRI

Distinguishing bipolar and unipolar depression as early as possible is fundamental for correct clinical choices and consequently better short and long-term outcomes. Data show that even with highest efforts, this differential diagnosis in the clinical setting has been precarious. Therefore, the development of more objective markers to support the differential diagnosis of bipolar and unipolar depression is mandatory. We employed resting-state functional connectivity analysis to select and directly compare alterations suggested in main large-scale networks in depressed bipolar I and unipolar patients in contrast to age- and gender-matched controls. Although displaying similar symptoms, groups were clearly distinguished by unique region-specific changes in these networks. Bipolar patients were characterized by increased functional connectivity in the frontoparietal network, a central executive and externally-oriented network. Unipolar patients presented increased functional connectivity in the default mode network, an introspective and self-referential network. The latter also presented reduced connectivity in the cingulo-opercular network to default mode regions, a network involved in dynamic switching between default mode and executive-related demands. Additionally, connectivity changes in unipolar patients significantly correlated to the number of previous depressive episodes. In the dynamic functional connectivity analysis, performed with sliding window methodology, regional alterations were majorly sustained, supporting the stability of findings and encouraging further development of such “network fingerprints” for the differential diagnosis of depression.