Ancestral Exposure to Stress Generates New Behavioral Traits and a Functional Hemispheric Dominance Shift
Bibliographic record
Abstract
In a continuously stressful environment, the effects of recurrent prenatal stress (PS) accumulate across generations and generate new behavioral traits in the absence of genetic variation. Here, we investigated if PS or multigenerational PS across 4 generations differentially affect behavioral traits, laterality, and hemispheric dominance in male and female rats. Using skilled reaching and skilled walking tasks, 3 findings support the formation of new behavioral traits and shifted laterality by multigenerational stress. First, while PS in the F1 generation did not alter paw preference, multigenerational stress in the F4 generation shifted paw preference to favor left-handedness only in males. Second, multigenerational stress impaired skilled reaching and skilled walking movement abilities in males, while improving these abilities in females beyond the levels of controls. Third, the shift toward left-handedness in multigenerationally stressed males was accompanied by increased dendritic complexity and greater spine density in the right parietal cortex. Thus, cumulative multigenerational stress generates sexually dimorphic left-handedness and dominance shift toward the right hemisphere in males. These findings explain the origins of apparently heritable behavioral traits and handedness in the absence of DNA sequence variations while proposing epigenetic mechanisms.
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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 | 0.000 |
| 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".