Depressive symptom trajectory following romantic relationship breakup and effects of rumination, neuroticism and cognitive control.

Studying individuals who recently experienced a romantic reltionship breakup allows us to investigate mood disturbances in otherwise healthy individuals. In our study, we aimed to identify distinct depressive symptom trajectories following breakup and investigate whether these trajectories relate to personality traits and cognitive control. Subjects (n = 87) filled out questionnaires (RRS-NL-EXT trait rumination and NEO-FFI neuroticism) and performed cognitive tasks (trail making test, Stroop task) during a period of 30 weeks. To identify distinct depressive symptom trajectories ('trajectory groups'), we performed K-means clustering on the consecutive (assessed every 2 weeks) Major Depression Inventory scores. This resulted in four trajectory groups; 'resilience', 'fast recovery', 'slow recovery' and 'chronic distress'. The 'slow recovery group' and the 'chronic distress group' were found to have higher neuroticism and trait rumination levels compared to the 'resilience group', and the 'chronic distress group' also had higher neuroticism levels than the 'fast recovery group'. Moreover, the 'chronic distress group' showed worse overall trail making test performance than the 'resilience group'. Taken together, our findings show that distinct patterns of depressive symptom severity can be observed following breakup and that personality traits and cognitive flexibility seem to play a role in these depressive symptom patterns.

The Dynamics of Functional Brain Networks Associated With Depressive Symptoms in a Nonclinical Sample.

Brain function depends on the flexible and dynamic coordination of functional subsystems within distributed neural networks operating on multiple scales. Recent progress has been made in the characterization of functional connectivity (FC) at the whole-brain scale from a dynamic, rather than static, perspective, but its validity for cognitive sciences remains under debate. Here, we analyzed brain activity recorded with functional Magnetic Resonance Imaging from 71 healthy participants evaluated for depressive symptoms after a relationship breakup based on the conventional Major Depression Inventory (MDI). We compared both static and dynamic FC patterns between participants reporting high and low depressive symptoms. Between-group differences in static FC were estimated using a standard pipeline for network-based statistic (NBS). Additionally, FC was analyzed from a dynamic perspective by characterizing the occupancy, lifetime, and transition profiles of recurrent FC patterns. Recurrent FC patterns were defined by clustering the BOLD phase-locking patterns obtained using leading eigenvector dynamics analysis (LEiDA). NBS analysis revealed a brain subsystem exhibiting significantly lower within-subsystem correlation values in more depressed participants (high MDI). This subsystem predominantly comprised connections between regions of the default mode network (i.e., precuneus) and regions outside this network. On the other hand, LEiDA results showed that high MDI participants engaged more in a state connecting regions of the default mode, memory retrieval, and frontoparietal network (p-FDR = 0.012); and less in a state connecting mostly the visual and dorsal attention systems (p-FDR = 0.004). Although both our analyses on static and dynamic FC implicate the role of the precuneus in depressive symptoms, only including the temporal evolution of BOLD FC helped to disentangle over time the distinct configurations in which this region plays a role. This finding further indicates that a holistic understanding of brain function can only be gleaned if the temporal dynamics of FC is included.

Reduced spatiotemporal brain dynamics are associated with increased depressive symptoms after a relationship breakup.

Depressive symptoms following a stressful life event, such as a relationship breakup, are common, and constitute a potent risk factor for the onset of a major depressive episode. Resting-state neuroimaging studies have increasingly identified abnormal whole-brain communication in patients with depression, but it is currently unclear whether depressive symptoms in individuals without a clinical diagnosis have reliable neural underpinnings. We investigated to what extent the severity of depressive symptoms in a non-clinical sample was associated with imbalances in the complex dynamics of the brain during rest. To this end, a novel intrinsic ignition approach was applied to resting-state neuroimaging data from sixty-nine participants with varying degrees of depressive symptoms following a relationship breakup. Ignition-based measures of integration, hierarchy, and metastability were calculated for each participant, revealing a negative correlation between these measures and depressive ratings. We found that the severity of depressive symptoms was associated with deficits in the brain's capacity to globally integrate and process information over time. Furthermore, we found that increased depressive symptoms were associated with reduced spatial diversity (i.e., hierarchy) and reduced temporal variability (i.e., metastability) in the functional organization of the brain. These findings suggest the merit of investigating constrained dynamical complexity as it is sensitive to the level of depressive symptoms even in a non-clinical sample.