PARASYMPATHETIC INFLUENCE ON COGNITIVE AGING IS MODERATED BY SYMPATHETIC ACTIVITY, ESPECIALLY IN EARLY MIDLIFE
Bibliographic record
Abstract
Abstract The two branches of the autonomic nervous system (ANS) have been individually linked to age-related changes in cognitive functioning: The parasympathetic nervous system (PNS) is thought to support healthy cognitive aging, whereas the sympathetic nervous system (SNS) has been linked to heightened cognitive decline. Despite these separate findings and despite the integrative nature of the ANS, little work has examined the two branches simultaneously to better understand their interactive effects on age-related cognitive changes. We examined cognitive change in two waves of the MIDUS cognitive project and indexed PNS and SNS activity from heart rate variability and epinephrine levels (respectively) from the MIDUS biomarker project (n = 764, 56% female, mean age = 54.1 years). Our findings indicate that higher PNS levels attenuate cognitive decline, but only among individuals with low SNS levels; at higher SNS levels, the beneficial effects of the PNS are blocked. Further, lower PNS levels can be somewhat compensated for by increased SNS levels. This pattern was most robust among individuals transitioning to mid-life (i.e., 35-40 years old at the initial cognitive test). These results suggest that interventions targeting the ANS as a modifiable factor in cognitive aging should consider both ANS branch’s effects simultaneously, particularly in the early stages of midlife.
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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".