348 Alexithymia impacts vulnerability for cognitive decline in healthy elders via frontal lobe connectivity during response inhibition, especially in women
Bibliographic record
Abstract
OBJECTIVES/GOALS: This project aimed to examine the impacts of biological sex and alexithymia on frontal lobe connectivity in executive functioning (EF)-related neural networks during successful inhibition as a means to index vulnerability for future cognitive decline. METHODS/STUDY POPULATION: Healthy, cognitively intact older adults (n=43, 33 female, Mage=79) completed the 20-item Toronto Alexithymia Scale (TAS-20) and the stop-signal task in this study. We used electroencephalography (EEG) source estimation to investigate EF-related frontal connectivity during successful inhibition in stop-signal task trials. Connectivity was measured in bilateral frontal ROIs relevant to inhibition using time series correlations over the N200 (186-350ms) and P300 (340-616ms) time windows, associated with the inhibitory subprocesses of conflict processing and performance evaluation, respectively. RESULTS/ANTICIPATED RESULTS: Those with higher alexithymia, as measured by the difficulty identifying feelings (DIF) facet of the TAS-20, had lower right anterior cingulate cortex (ACC)-left superior frontal gyrus (SFG) connectivity in the P300 window, suggesting impaired performance evaluation. Further, in females specifically, those with higher DIF had greater right inferior frontal gyrus (rIFG)-bilateral ACC connectivity in the N200 window than those with lower DIF, suggesting greater resources were allocated for conflict processing and inhibition. Right ACC-rIFG connectivity also correlated with better stop accuracy and faster stop-signal reaction time, supporting this network’s role in successful inhibition. DISCUSSION/SIGNIFICANCE: Overall, during successful inhibition, higher DIF was associated with reduced performance monitoring efficiency as well as greater resource allocation for conflict processing during motor stopping in women only. Thus, alexithymia (via DIF) may exacerbate age-related EF dysfunction and risk for future cognitive decline, especially for females.
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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) | 0.003 | 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".