Baseline brain perfusion and brain structure in patients with major depression: a multimodal magnetic resonance imaging study
Bibliographic record
Abstract
BACKGROUND: Abnormal regional cerebral blood flow (rCBF) and grey matter volume have been frequently reported in patients with major depressive disorder (MDD). However, it is unclear to what extent structural and functional change co-occurs in patients with MDD and whether markers of neural activity, such as rCBF, can be predicted by structural change. METHODS: Using MRI, we investigated resting-state rCBF and brain structure in patients with MDD and healthy controls between July 2008 and January 2013. We acquired perfusion images obtained with continuous arterial spin labelling, used voxel-based morphometry to assess grey matter volume and integrated biological parametric mapping analyses to investigate the impact of brain atrophy on rCBF. RESULTS: We included 43 patients and 29 controls in our study. Frontotemporal grey matter volume was reduced in patients compared with controls. In patients, rCBF was reduced in the anterior cingulate and bilateral parahippocampal areas and increased in frontoparietal and striatal regions. These abnormalities were confirmed by analyses with brain volume as a covariate. In patients with MDD there were significant negative correlations between the extent of depressive symptoms and bilateral parahippocampal rCBF. We found a positive correlation between depressive symptoms and rCBF for right middle frontal cortical blood flow. LIMITATIONS: Medication use in patients has to be considered as a limitation of our study. CONCLUSION: Our data suggest that while changes of cerebral blood flow and brain volume co-occur in patients with MDD, structural change is not sufficient to explain altered neural activity in patients at rest. Abnormal brain structure and function in patients with MDD appear to reflect distinct levels of neuropathology.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".