P1‐332: EMOTIONAL STROOP PERFORMANCE: FURTHER EVIDENCE FOR DISTINCT COGNITIVE PATTERNS IN DEPRESSED AND NON‐DEPRESSED AMCI
Bibliographic record
Abstract
It is well-established that individuals with amnestic mild cognitive impairment (aMCI) or late-life depression (LLD) are at high risk for developing dementia. aMCI is a highly heterogeneous syndrome: patients may manifest a variety of different cognitive and neuropsychiatric symptoms, some of which may resemble those of LLD. Emerging research suggests that patients with aMCI and concomitant depressive symptoms (aMCI/D+) may be an identifiable subtype of prodromal dementia that is distinct from that of non-depressed aMCI and LLD. Indeed, these groups perform differently on tests of episodic memory (Callahan et al., 2012a), semantic memory (Brunet et al., 2011; Callahan et al., 2012b) and inhibition (Hudon et al., 2008). Furthermore, aMCI and aMCI/D+ evolve differently over time (Steffens, 2012). The present study aimed to further characterize aMCI/D+ by investigating patients' cognitive processing of emotional stimuli. Twenty-nine MCI, 14 aMCI/D+, 10 LLD and 15 healthy elderly controls (CONT) performed an emotional Stroop task in which blocks of different-colored positive, negative and neutral words were presented on a computer screen. Participants were instructed to name the color of each word as quickly as possible. Response time (RT) to name each color was recorded. Afterward, subjects were asked to rate the emotional intensity of each word on a scale from 1 (not intense) to 9 (very intense) to verify whether task performance is modulated by stimulus intensity. All three patient groups were slower than CONT in completing the emotional Stroop task. CONT subjects had longer RTs on negative compared to neutral blocks. Latencies of aMCI/D+ patients were longer on negative than neutral and positive blocks. Performance of aMCI and LLD groups were similar on emotional and neutral blocks. These results were independent of words' intensity ratings. This study is the first to investigate emotional Stroop performance in participants with probable prodromal dementia. The results converge with those of prior studies to support the notion that aMCI/D+ may represent an identifiable subgroup distinct from aMCI and LLD. Increasing our understanding of the features of aMCI/D+ through additional research is essential to elucidate the heterogeneity of prodromal dementia and to optimize preven tion and treatment plans.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".