Abnormal Structural Networks Characterize Major Depressive Disorder: A Connectome Analysis
Abstract
Background Major depressive disorder (MDD) has been shown to be associated with a disrupted topological organization of functional brain networks. However, little is known regarding whether these changes have a structural basis. Diffusion tensor imaging (DTI) enables comprehensive whole-brain mapping of the white matter tracts that link regions distributed throughout the entire brain, the so-called human connectome. Methods We examined whole-brain structural networks in a cohort of 95 MDD outpatients and 102 matched control subjects. Structural networks were represented by an 84 × 84 connectivity matrix representing probabilistic white matter connections between 84 parcellated cortical and subcortical regions using DTI tractography. Network-based statistics were used to assess differences in the interregional connectivity matrix between the two groups, and graph theory was used to examine overall topological organization. Results Our network-based statistics analysis demonstrates lowered structural connectivity within two distinct brain networks that are present in depression: the first primarily involves the regions of the default mode network and the second comprises the frontal cortex, thalamus, and caudate regions that are central in emotional and cognitive processing. These two altered networks were observed in the context of an overall preservation of topology as reflected as no significant group differences for the graph-theory measures. Conclusions This is the first report to use DTI to show the structural connectomic alterations present in MDD. Our findings highlight that altered structural connectivity between nodes of the default mode network and the frontal-thalamo-caudate regions are core neurobiological features associated with MDD.
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In depression, connectivity within the DMN and fronto-thalamo-caudate regions was reduced, community structure was rearranged, and hubs were altered.
“In depression, connectivity within the default mode network and fronto-thalamo-caudate regions was reduced, 57 community structure was rearranged, 65 and hubs were altered.64”
From Graph theory analysis of complex brain networks: new concepts in brain mapping applied to neurosurgery (2016) · cites this paper as [57]
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References 46 · Cited by 367
- Authors
- Korgaonkar, M. S., Fornito, A., Williams, L. M., & Grieve, S. M.
- Affiliations
- The University of Sydney (AU)
- Monash University (AU)
- Stanford Medicine (US)
- Corresponding author
- Grieve, Stuart M.
- Venue
- Biological Psychiatry
- Publisher
- Elsevier BV
- Published
- 2014-10
- Volume
- 76
- Issue
- 7
- Pages
- 567-574
- ISSN
- 0006-3223 (ISSN-L)
- OpenAlex
- W2168489054
- Cited by
- 367
- References
- 46
- Citations by year
- 2026: 20 · 2025: 24 · 2024: 24 · 2023: 25 · 2022: 29 · 2021: 37 · 2020: 32 · 2019: 36 · 2018: 39 · 2017: 33 · 2016: 31 · 2015: 21 · 2014: 15
- FWCI
- 18.60
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Biological Psychiatry (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Health Sciences › Medicine › Pharmacology › Treatment of Major Depression
- Keywords
- major depressive disorder, structural connectome, white matter connectivity, default mode network, network-based statistics, graph theory, brain network topology, diffusion tensor tractography
- MeSH terms
- Adolescent, Adult, Brain, Depressive Disorder, Major, Major Depressive Disorder, Female, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Nerve Net, Statistics as Topic, Young Adult, Diffusion Tensor Imaging, Connectome, White Matter
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