Brain functional dynamics linked to major depression and anxiety: cross-sectional and longitudinal associations over 9 years.
Gaviria, J.; van Wingen, G.; Jansen, R.; Labus, J. S.; Penninx, B.
Show abstract
Background. Resting-state fMRI (rs-fMRI) co-activation patterns (CAPs) capture recurrent whole-brain states that may index neurobiological substrates of affective psychopathology, yet whether their dynamics co-evolve with symptom severity over the long-term course of depression and anxiety remains unknown. Methods. We analyzed rs-fMRI and clinical data from 340 participants in the NESDA cohort (228 with a depressive and/or anxiety disorder, AFF) at baseline (Y0), 2-year (Y2), and 9-year (Y9) follow-up. Four CAPs were identified and validated. CAP dwell time and entries were related to depression (IDS), anxiety (BAI), and fear (FQ) severity between subjects and within individuals. Results. At baseline, attention-somatomotor (AT-SMCAP) dwell time was inversely associated with depression severity in CTR (rho = -0.29, q < 0.05) but not AFF (rho = 0.09, q = 0.79). Longitudinally, group-level trajectories showed no CAP-symptom coupling; it emerged only within individuals, where increases in frontoparietal-default-mode (FP-DMCAP) dwell time tracked worsening depression in AFF only (Y2 to Y9: rho = 0.47, q < 0.01). Conclusions. AT-SMCAP distinguished health from illness cross-sectionally, whereas FP-DMCAP indexed illness course within individuals, effects not captured by group-averaged analyses. These findings highlight individual-level CAP dynamics as relevant to longitudinal brain-symptom coupling, with implications for precision psychiatry.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Neuroinflammation in the amygdala is associated with recent depressive symptoms 93%
- Maladaptive avoidance learning in the orbitofrontal cortex in adolescents with major depression 93%
- Machine learning models identify multimodal measurements highly predictive of transdiagnostic symptom severity for mood, anhedonia, and anxiety 93%
Similar papers in this journal
- Causes and consequences of major depressive disorder: An encompassing Mendelian randomization study 92%
- Neuroimaging Insights into Brain Mechanisms of Early-onset Restrictive Eating Disorders 91%
- A methylome-wide association study of major depression with out-of-sample case-control classification and trans-ancestry comparison 91%
Similar papers in this journal
- Brain-Symptom Network Models of Depressive Symptoms: Understanding Heterogeneity and Clinical Implications 95%
- Neurocognitive deficits, psychotrauma, and inflammation shape major depressive disorder and its phenome features 94%
- Disrupted Limbic-Prefrontal Effective Connectivity in Response to Fearful Faces in Lifetime Depression 94%
Similar papers in this journal
- Higher amplitudes of visual networks are associated with trait but not state- depression. 95%
- Increased Insular Functional Connectivity During Repetitive Negative Thinking in Major Depression and Healthy Volunteers 94%
- Effective connectivity during faces processing in major depression – distinguishing markers of pathology, risk, and resilience 94%
Similar papers in this journal
- The Influence of Phenotyping Method on Structural Neuroimaging Associations with Depression in UK Biobank 95%
- Applying Machine-Learning and Deep-Learning to Predict Depression from Brain MRI and Identify Depression-Related Brain Biology 94%
- Paving the way for precision treatment of psychiatric symptoms with functional connectivity neurofeedback 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.