Emotional processing and executive functions in major depressive disorder: dorsal prefrontal activity correlates with performance in the intra–extra dimensional set shift
Bibliographic record
Abstract
UNLABELLED: Heinzel A, Northoff G, Boeker H, Boesiger P, Grimm S. Emotional processing and executive functions in major depressive disorder: dorsal prefrontal activity correlates with performance in the intra-extra dimensional set shift. OBJECTIVE: Major depressive disorder (MDD) is characterised by predominately negatively valenced emotional symptoms that are often accompanied by cognitive impairments. We posited that cognitive impairments in MDD are related to altered emotional processing in prefrontal cortex. METHODS: We compared 20 medication-free patients with MDD and 29 matched healthy controls. Both groups performed an emotional task during functional magnetic resonance imaging (fMRI). Furthermore, they completed the intra-extra dimensional set shift (IED) test probing for cognitive impairments. Then we correlated the results of the IED with the changes in fMRI BOLD signal in MDD patients and healthy subjects. RESULTS: The subcategory of the IED applying extradimensional shift (EDS) showed a divergent performance of the MDD group committing significantly more errors than the control group. Correlating the EDS errors with fMRI signal changes, the healthy subjects showed a positive correlation with the right ventrolateral prefrontal cortex and the right orbitofrontal cortex. MDD subjects, in contrast, showed a positive correlation in right dorsolateral prefrontal cortex (DLPFC) and a negative correlation in the left dorsomedial prefrontal cortex (DMPFC). CONCLUSION: We hypothesise that the differential correlation in healthy controls and MDD patients may reflect the use of different strategies in their performance. The impaired executive functions, as reflected by altered processing in right DLPFC and left DMPFC, may implicitly influence emotional processing in patients suffering from MDD.
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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) | 0.000 | 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".