ArticleFrontiers in psychiatry2021
Modeling Heterogeneous Brain Dynamics of Depression and Melancholia Using Energy Landscape Analysis.
Article in Frontiers in psychiatry, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Characteristic spatiotemporal features of large-scale functional network architecture in posttraumatic stress disorder.Translational psychiatry · 2026Article
- Noninvasive reduction of neural rigidity alters autistic behaviors in humans.Nature neuroscience · 2025Article
- Comparison of Large Language Model with Aphasia.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Linking energetic instability to compositional changes in biological communities.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Energy landscape analysis based on the Ising model: Tutorial review.PLOS complex systems · 2025Article
- The brain selectively allocates energy to functional brain networks under cognitive control.Scientific reports · 2024Article
- FNIRS-Based Energy Landscape Analysis to Signify Brain Activity Dynamics of Individuals With Depression.CNS neuroscience & therapeutics · 2024Article
- Article
- Aberrant brain dynamics in individuals with clinical high risk of psychosis.Schizophrenia bulletin open · 2024Article
- Manifold alteration between major depressive disorder and healthy control subjects using dynamic mode decomposition in resting-state fMRI data.Frontiers in psychiatry · 2024Article
- Aberrant brain dynamics of large-scale functional networks across schizophrenia and mood disorder.NeuroImage. Clinical · 2024Article
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Authors and funding
10 authors.
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Abstract
Our current understanding of melancholic depression is shaped by its position in the depression spectrum. The lack of consensus on how it should be treated-whether as a subtype of depression, or as a distinct disorder altogethe-interferes with the recovery of suffering patients. In this study, we analyzed brain state energy landscape models of melancholic depression, in contrast to healthy and non-melancholic energy landscapes. Our analyses showed significant group differences on basin energy, basin frequency, and transition dynamics in several functional brain networks such as basal ganglia, dorsal default mode, and left executive control networks. Furthermore, we found evidences suggesting the connection between energy landscape characteristics (basin characteristics) and depressive symptom scores (BDI-II and SHAPS). These results indicate that melancholic depression is distinguishable from its non-melancholic counterpart, not only in terms of depression severity, but also in brain dynamics.
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