Modeling Heterogeneous Brain Dynamics of Depression and Melancholia Using Energy Landscape Analysis
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 an...
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Frontiers Media S.A.
2021
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oai:doaj.org-article:612dff4db77144ae96492ba05a163c732021-12-01T02:09:10ZModeling Heterogeneous Brain Dynamics of Depression and Melancholia Using Energy Landscape Analysis1664-064010.3389/fpsyt.2021.780997https://doaj.org/article/612dff4db77144ae96492ba05a163c732021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fpsyt.2021.780997/fullhttps://doaj.org/toc/1664-0640Our 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.Paul Rossener RegoniaPaul Rossener RegoniaMasahiro TakamuraMasahiro TakamuraTakashi NakanoTakashi NakanoNaho IchikawaAlan FerminGo OkadaYasumasa OkamotoYasumasa OkamotoShigeto YamawakiKazushi IkedaJunichiro YoshimotoFrontiers Media S.A.articledepressionmelancholiaenergy landscape analysisresting state fMRIfunctional brain networkPsychiatryRC435-571ENFrontiers in Psychiatry, Vol 12 (2021) |
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DOAJ |
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EN |
| topic |
depression melancholia energy landscape analysis resting state fMRI functional brain network Psychiatry RC435-571 |
| spellingShingle |
depression melancholia energy landscape analysis resting state fMRI functional brain network Psychiatry RC435-571 Paul Rossener Regonia Paul Rossener Regonia Masahiro Takamura Masahiro Takamura Takashi Nakano Takashi Nakano Naho Ichikawa Alan Fermin Go Okada Yasumasa Okamoto Yasumasa Okamoto Shigeto Yamawaki Kazushi Ikeda Junichiro Yoshimoto Modeling Heterogeneous Brain Dynamics of Depression and Melancholia Using Energy Landscape Analysis |
| description |
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. |
| format |
article |
| author |
Paul Rossener Regonia Paul Rossener Regonia Masahiro Takamura Masahiro Takamura Takashi Nakano Takashi Nakano Naho Ichikawa Alan Fermin Go Okada Yasumasa Okamoto Yasumasa Okamoto Shigeto Yamawaki Kazushi Ikeda Junichiro Yoshimoto |
| author_facet |
Paul Rossener Regonia Paul Rossener Regonia Masahiro Takamura Masahiro Takamura Takashi Nakano Takashi Nakano Naho Ichikawa Alan Fermin Go Okada Yasumasa Okamoto Yasumasa Okamoto Shigeto Yamawaki Kazushi Ikeda Junichiro Yoshimoto |
| author_sort |
Paul Rossener Regonia |
| title |
Modeling Heterogeneous Brain Dynamics of Depression and Melancholia Using Energy Landscape Analysis |
| title_short |
Modeling Heterogeneous Brain Dynamics of Depression and Melancholia Using Energy Landscape Analysis |
| title_full |
Modeling Heterogeneous Brain Dynamics of Depression and Melancholia Using Energy Landscape Analysis |
| title_fullStr |
Modeling Heterogeneous Brain Dynamics of Depression and Melancholia Using Energy Landscape Analysis |
| title_full_unstemmed |
Modeling Heterogeneous Brain Dynamics of Depression and Melancholia Using Energy Landscape Analysis |
| title_sort |
modeling heterogeneous brain dynamics of depression and melancholia using energy landscape analysis |
| publisher |
Frontiers Media S.A. |
| publishDate |
2021 |
| url |
https://doaj.org/article/612dff4db77144ae96492ba05a163c73 |
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