Baseline functional connectivity in resting state networks associated with depression and remission status after 16 weeks of pharmacotherapy: A CAN-BIND Report
Bibliographic record
Abstract
Abstract Understanding the neural underpinnings of major depressive disorder (MDD) and its treatment could improve treatment outcomes. While numerous studies have been conducted, findings are variable and large sample replications scarce. We aimed to replicate and extend altered functional connectivity findings in the default mode, salience and cognitive control networks (DMN, SN, and CCN respectively) associated with MDD and pharmacotherapy outcomes in a large, multi-site sample. Resting-state fMRI data were collected from 129 patients and 99 controls through the Canadian Biomarker Integration Network in Depression (CAN-BIND) initiative. Symptoms were assessed with the Montgomery-Åsberg Depression Rating Scale (MADRS). Connectivity was measured as correlations between four seeds (anterior and posterior DMN, SN and CCN) and all other brain voxels across participants. Partial least squares, a multivariate statistical technique, was used to compare connectivity prior to treatment between patients and controls, and between patients reaching remission early (MADRS ≤ 10 within 8 weeks), late (MADRS ≤ 10 within 16 weeks) or not at all. We replicated previous findings of altered connectivity in the DMN, SN and CCN in patients. In addition, baseline connectivity of the anterior/posterior DMN and SN seeds differentiated patients with different treatment outcomes. Weaker connectivity within the anterior DMN and between the anterior DMN and the SN and CCN characterised early remission; stronger connectivity within the SN and weaker connectivity between the SN and the DMN and CCN was related to late remission, of which the weaker SN – anterior DMN connectivity might specifically be associated with remission to dual pharmacotherapy; and connectivity strength between the posterior DMN and cingulate areas distinguished all three groups, with early remitters showing the strongest connections and non-remitters the weakest. The stability of these baseline patient differences was established in the largest single-site subsample of the data. Our replication and extension of altered connectivity within and between the DMN, SN and CCN highlighted previously reported and new differences between patients with MDD and controls, and revealed features that might predict remission prior to pharmacotherapy. Trial registration ClinicalTrials.gov: NCT01655706 .
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".