| Title: | The neuroimaging correlates of depression established across six large-scale population datasets |
| Journal: | Nature Mental Health |
| Published: | 13 Jul 2026 |
| DOI: | https://doi.org/10.1038/s44220-026-00680-y |
| URL: | https://www.nature.com/articles/s44220-026-00680-y.pdf |
Publication 20289
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Abstract
Depression has been linked to reduced size of subcortical regions and abnormal functional connectivity in frontal and default mode networks. However, recent meta-analyses have failed to identify significant converging correlates of depression across the literature such that a conclusive mapping of the neuroimaging correlates of depression remains elusive. We leveraged 23,417 participants across 6 population datasets to comprehensively establish the neuroimaging correlates of depression. We found reductions in gray matter volume/cortical surface area associated with depression in the frontal cortex, anterior cingulate and insula, confirming previous studies showing the importance of prefrontal and default mode regions in depression. Our findings demonstrate multiple surprising results, including a lack of depression correlates in subcortical brain regions and significant depression correlates in somatomotor and visual regions. Overall, these results shed new light on key brain regions involved in the pathophysiology of depression, updating our understanding of the neuroimaging correlates of depression symptoms.</p>
17 Authors
- Kassandra Miyoko Hamilton
- Xiaoke Luo
- Ty Easley
- Fyzeen Ahmad
- Thomas Guo
- Setthanan Jarukasemkit
- Hailey Modi
- Samuel Naranjo Rincón
- Cabria Shelton
- Lyn Stahl
- Zijian Wang
- Yuling Zhu
- Petra Lenzini
- Deanna M. Barch
- Yvette I. Sheline
- Kayla Hannon
- Janine D. Bijsterbosch
1 Application
| Application ID | Title |
|---|---|
| 47267 | Cross-diagnostic and cross-platform multimodal analysis of UK Biobank imaging data |
Enabling scientific discoveries that improve human health