Contrasting emotion processing and executive functioning in attention-deficit/hyperactivity disorder and bipolar disorder.
Bibliographic record
Abstract
Attention-deficit/hyperactivity disorder (ADHD) and bipolar disorder (BD) are highly comorbid and share executive function and emotion processing deficits, complicating diagnoses despite distinct clinical features. We compared performance on an oculomotor task that assessed these processes to capture subtle differences between ADHD and BD. The interaction between emotion processing and executive functioning may be informative because, although these processes overlap anatomically, certain regions that are compromised in each network are different in ADHD and BD. Adults, aged 18-62, with ADHD (n = 22), BD (n = 20), and healthy controls (n = 21) performed an interleaved pro- and antisaccade task (looking toward vs. looking away from a visual target, respectively). Task irrelevant emotional faces (fear, happy, sad, neutral) were presented on a subset of trials either before or with the target. The ADHD group made more direction errors (looked in the wrong direction) than controls. Presentation of negatively valenced (fear, sad) and ambiguous (neutral) emotional faces increased saccadic reaction time in BD only compared to controls, whereas longer presentation of sad faces modestly increased group differences. The antisaccade task differentiated ADHD from controls. Emotional processing further impaired processing speed in BD. We propose that the dorsolateral prefrontal cortex is critical in both processing systems, but the inhibitory signal this region generates is impacted by dysfunction in the emotion processing network, possibly at the orbitofrontal cortex, in BD. These results suggest there are differences in how emotion processing and executive functioning interact, which could be utilized to improve diagnostic specificity. (PsycINFO Database Record
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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".