Large Individual Differences in Functional Connectivity in the Context of Major Depression and Antidepressant Pharmacotherapy
Bibliographic record
Abstract
Abstract Clinical studies of major depression (MD) often examine differences between groups whilst ignoring within-group variation. However, inter-individual differences in brain function are increasingly recognised as important and may impact effect sizes related to group effects. Here, we examine the magnitude of individual differences in relation to group differences that are commonly investigated (e.g., related to MD diagnosis and treatment response). Functional MRI data from 107 participants (63 female, 44 male) were collected at baseline, 2 and 8 weeks during which patients received pharmacotherapy (escitalopram, N=68), and controls (N=39) received no intervention. The unique contributions of different sources of variation were examined by calculating how much variance in functional connectivity was shared across all participants and sessions, within/across groups (patients vs controls, responders vs non-responders, female vs male participants), recording sessions and individuals. Individual differences and common connectivity across groups, sessions and participants contributed most to the explained variance (>95% across analyses). Group differences related to MD diagnosis, treatment response and biological sex made significant but small contributions (0.3-1.2%). High individual variation was present in multimodal association areas, while low individual variation characterized primary sensorimotor regions. Group differences were much smaller than individual differences in the context of MD and its treatment. These results could be linked to the variable findings and difficulty translating research on MD to clinical practice. Future research should examine brain features with low and high individual variation in relation to psychiatric symptoms and treatment trajectories to explore the clinical relevance of the individual differences identified here. Significance statement Studies on major depression often investigate differences in brain function between groups (e.g., those with/without a diagnosis) with the aim of better understanding this prevalent condition. Our study shows that group differences only tell part of the story, by highlighting strong common and individually unique features of brain network organization, relative to surprisingly subtle features of diagnosis and treatment success. From the overall explained variation in brain connectivity, about 50% was shared across everyone, while another 45% was unique to individuals. Only ∼5% could be attributed to diagnosis, treatment success and biological sex differences. Our results suggest that examining individual differences, and their potential clinical relevance, alongside group differences may bring us closer to improving clinical outcomes for major depression. 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 | 0.005 |
| 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 | 0.000 |
| 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".