ArticleJournal of psychiatric research2015
Subcortical volumes differentiate Major Depressive Disorder, Bipolar Disorder, and remitted Major Depressive Disorder.
Article in Journal of psychiatric research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 4 of them syntheses that pooled it.
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Who cites it
42 citing papers in PubMed, 4 syntheses or guidelines pooled it, 98 citations in OpenAlex.
- Evaluation of Risk of Bias in Neuroimaging-Based Artificial Intelligence Models for Psychiatric Diagnosis: A Systematic Review.JAMA network open · 2023Pooled it
- Using structural MRI to identify bipolar disorders - 13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group.Molecular psychiatry · 2020Pooled it
- Towards a brain-based predictome of mental illness.Human brain mapping · 2020Pooled it
- Detecting Neuroimaging Biomarkers for Depression: A Meta-analysis of Multivariate Pattern Recognition Studies.Biological psychiatry · 2017Pooled it
- Cell death pathways in the pathogenesis of depression: mechanisms and therapeutic implications.Frontiers in cell and developmental biology · 2026Review
- Biomarkers of bipolar disorder in omics and neuroimaging.Journal of pharmaceutical analysis · 2025Review
- The effects of estradiol on subcortical brain volumes in perimenopausal-onset depression.Journal of affective disorders · 2025Article
- The X chromosome's influences on the human brain.Science advances · 2025Article
- Machine learning with multiple modalities of brain magnetic resonance imaging data to identify the presence of bipolar disorder.Journal of affective disorders · 2025Article
- Investigating biomarkers of mitochondrial and aging-related genes in major depressive disorder through bioinformatics analysis.Frontiers in psychiatry · 2025Article
- Investigating sex-related differences in brain structure and function in bipolar I disorder using multimodal MRI.BMC psychiatry · 2024Article
- The effects of psychotherapy for anhedonia on subcortical brain volumes measured with ultra-high field MRI.Journal of affective disorders · 2024Article
- Alterations in subcortical magnetic susceptibility and disease-specific relationship with brain volume in major depressive disorder and schizophrenia.Translational psychiatry · 2024Article
- Article
- Neuroanatomical dimensions in medication-free individuals with major depressive disorder and treatment response to SSRI antidepressant medications or placebo.Nature. Mental health · 2024Article
- Automatic Diagnosis of Major Depressive Disorder Using a High- and Low-Frequency Feature Fusion Framework.Brain sciences · 2023Article
- Sampling inequalities affect generalization of neuroimaging-based diagnostic classifiers in psychiatry.BMC medicine · 2023Article
- Sex differences in brain volumes and psychological distress: The first hundred brains cohort of the longitudinal adolescent brain study.Neuroimage. Reports · 2023Article
- An Overview of Bipolar Disorder Diagnosis Using Machine Learning Approaches: Clinical Opportunities and Challenges.Iranian journal of psychiatry · 2023Article
- Unsupervised cross-domain functional MRI adaptation for automated major depressive disorder identification.Medical image analysis · 2023Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
Abstract
Subcortical gray matter regions have been implicated in mood disorders, including Major Depressive Disorder (MDD) and Bipolar Disorder (BD). It is unclear, however, whether or how these regions differ among mood disorders and whether such abnormalities are state- or trait-like. In this study, we examined differences in subcortical gray matter volumes among euthymic BD, MDD, remitted MDD (RMD), and healthy (CTL) individuals. Using automated gray matter segmentation of T1-weighted MRI images, we estimated volumes of 16 major subcortical gray matter structures in 40 BD, 57 MDD, 35 RMD, and 61 CTL individuals. We used multivariate analysis of variance to examine group differences in these structures, and support vector machines (SVMs) to assess individual-by-individual classification. Analyses yielded significant group differences for caudate (p = 0.029) and ventral diencephalon (VD) volumes (p = 0.003). For the caudate, both the BD (p = 0.004) and the MDD (p = 0.037) participants had smaller volumes than did the CTL participants. For the VD, the MDD participants had larger volumes than did the BD and CTL participants (ps < 0.005). SVM distinguished MDD from BD with 59.5% accuracy. These findings indicate that mood disorders are characterized by anomalies in subcortical gray matter volumes and that the caudate and VD contribute uniquely to differential affective pathology. Identifying abnormalities in subcortical gray matter may prove useful for the prevention, diagnosis, and treatment of mood disorders.
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