Brain network signatures of depressive symptoms

Depressive symptoms are common in the general population. Even in individuals who do not meet the criteria for a Major Depression Disorder (MDD), their symptoms are of clinical relevance because they increase the likelihood of progressing into a full-blown depressive episode, which in turn increases the prevalence of future episodes.
The studies in this thesis apply advanced computational methods to functional magnetic resonance imaging (fMRI) data to investigate the dynamics of network connectivity, with the aim of understanding what brain mechanisms make a person more vulnerable to depression.
Our results suggest that imbalances in whole-brain connectivity can already be linked to higher levels of depressive symptoms in healthy (undiagnosed) individuals. These imbalances correspond to a reduced dynamism in the overall functional organization of the brain, suggesting a link between a ‘rigid brain’ and rigid behavior, such as the lack of flexibility in cognitive and emotional responses that often accompanies depressive symptoms. Additionally, individual differences in the repertoire of brain states indicate that people with more depressive symptoms engage more in states related to self-referential thinking. This tendency was also observed in remitted patients during the transition into a depressive episode. This emphasizes that the present experience of depressive symptoms, whether in healthy individuals or MDD patients, is associated with changes in brain communication.
The findings of this thesis lead to a deeper understanding of the complex orchestration of brain communication and its changes concerning depressive symptomatology in clinical and nonclinical populations.