Association between cognitive function and performance on effort based decision making in patients with major depressive disorder treated with Vortioxetine
Bibliographic record
Abstract
It is well established that deficits in motivation, reward, and cognition are common during and in between syndromal episodes of depression as part of Major Depressive Disorder (MDD). Informed by evidence indicating functional and structural interconnectivity between cognitive and reward brain circuits, we preliminarily evaluate the association between measures of cognitive performance and reward/motivation. This is a post-hoc analysis of a primary study (i.e. the THINC-it sensitivity to change study). Adults (18–65 years of age) meeting DSM-5 criteria for MDD, single-episode or recurrent confirmed by M.I.N.I. with moderate severity or greater (i.e. Montgomery Asberg Depression Rating Scale ≥20). All eligible subjects received vortioxetine 10–20 mg open-label for 8 weeks. The Effort Expenditure Reward Task (EEfRT) was the principal measure of motivation and reward. We directly compare the effects of cognitive measures and depressive symptoms on effort-based decision-making using the THINC-it composite score and MADRS total score. Twenty-one participants with MDD (Mean age = 38.47, SD = 12.85) and 20 healthy volunteers (Mean age = 41.50, SD = 14.21) completed the optional EEfRT task. Amongst individuals with MDD, performance in processing speed, executive function (i.e. Trails B) and overall composite cognitive score was positively associated with the proportion of hard-task choices in the high reward condition (i.e. greater reward valuation). Across both groups, a greater probability (χ2 = 1.137) and magnitude of reward (χ2 = 0.045) was associated with increased effort (i.e. choosing the hard task more frequently). Using fully factored GEE models, we observed a positive association between performance on the Trails test (β = 2.223, SE = 0.928, p = 0.017) as well as the composite score (β = 0.978, SE = 0.0.459, p = 0.033), and greater effort for high rewards. In addition, it was observed that a positive association (i.e. greater effort for reward in higher probability) was observed with depressive symptoms and overall cognitive measures. Herein, we observed that an association exists between overall cognitive function, notably processing speed and executive function and reward function. Specifically, a greater effort for hard task rewards (using the EEfRT task) was manifested in individuals exhibiting higher levels of cognitive performance in a well-characterized sample of MDD treated with Vortioxetine.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".