A surprisingly simple computational model demonstrating how neurons self-organise and form connections. Image Credit: The University of Chicago
MDD (Major Depressive Disorder) is a common mental illness characterised by persistent feelings of sadness, a lack of interest in daily activities, low energy, and difficulty concentrating.
For a long time, researchers have studied both structural and functional differences in the brains of people who experience depression; most studies only focus on "static" measures, therefore producing a snapshot of brain activity. However, recent researchers have begun to examine brain dynamics, or how brain activity and connectivity change over time.
Exploring these dynamic changes will help researchers understand both state characteristics (which represent temporary changes associated with present symptom severity) and trait characteristics (long-term characteristics that may relate to the persistence or risk of relapse in developing depression).
The researchers examined the dynamic activity in the brain over time of MDD using advanced neuroimaging methods. They measured brain activity of the MDD population and the brains of healthy controls and compared the two groups to see what patterns of connectivity are associated with a person's symptom severity. They found that the MDD population experiences alterations in brain networks associated with emotion regulation, cognitive control, and self-reflection. Specifically the default mode network (DMN), frontoparietal network (FPN), salience network (SN), and dorsal attention network (DAN). Some of these changes varied with the current severity of depressive symptoms (state characteristics), while others were consistent across participants regardless of symptoms (trait characteristics),which may relate to the persistence of depressive patterns or risk of relapse.
These findings indicate that certain altered patterns of brain dynamics are present in MDD and that MDD is more than just a static condition.
Understanding these dynamic patterns of brain function has clinical value. Specifically, state characteristics could allow clinicians to monitor a patient's progress towards remission or to identify a patient's early changes in symptom severity; conversely, trait characteristics could enable clinicians to identify patients at risk for relapse or chronic depression.
Researchers have highlighted the importance of examining not only which brain regions show altered activity in MDD, but also how those brain regions interact over time, thereby offering insights for more accurate diagnoses and personalised treatment strategies.
Reference:
Javaheripour, N., Colic, L., Opel, N., et al. (2023). Altered brain dynamic in major depressive disorder: state and trait features. Translational Psychiatry. https://doi.org/10.1038/s41398-023-02540-0
Further reading:
Jiang, X., etal (2019). Connectome analysis of functional and structural hemispheric brain networks in major depressive disorder. Translational Psychiatry. https://doi.org/10.1038/s41398-019-0467-9