Differential stress response to psychological and physical stressors in children using spatial versus response-dependent navigation strategies
Bibliographic record
Abstract
Previous work from our lab has shown that basal cortisol levels are different between healthy young adults who spontaneously use caudate nucleus-dependent response strategies compared to young adults who use hippocampus-dependent spatial navigation strategies. Young adults who use caudate nucleus dependent strategies display lower basal cortisol levels compared to those who use hippocampus-dependent strategies. In the current study, we assessed navigation strategies in children using a virtual navigation task and measured cortisol at baseline as well as cortisol reactivity to both a psychological and to a physical stressor. Replicating what is observed in adults, we found that children who used caudate nucleus-dependent navigation strategies displayed lower cortisol levels at baseline compared to those who used hippocampus-dependent strategies. The psychological stressor, knowledge that a blood draw would be performed by a nurse, caused a significant increase in cortisol uniquely in response learners. The physical stressor, the actual blood draw, produced a significant increase in cortisol amongst spatial learners that was then comparable to levels observed in response learners. Lower baseline cortisol and higher cortisol psychological stress response observed amongst children who used response strategies may therefore reflect early biological changes during development which may have an impact later in life when considering risk for neuropsychiatric disorders.
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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 | 0.001 | 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".