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

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  • Sonsoles Alonso Martínez, University of Groningen
  • ,
  • Jan Bernard C. Marsman, University of Groningen
  • ,
  • Morten L. Kringelbach
  • Gustavo Deco, Pompeu Fabra University
  • ,
  • Gert J. ter Horst, University of Groningen

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.

Original languageEnglish
Article number102299
JournalNeuroImage: Clinical
Volume27
ISSN2213-1582
DOIs
Publication statusPublished - 2020

    Research areas

  • Depressive symptoms, Global integration, Non-clinical sample, Resting-state fMRI, Spatiotemporal dynamics, Whole-brain

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