A meta-analysis of sex differences in neonatal rodent ultrasonic vocalizations and the implication for the preclinical maternal immune activation model
Bibliographic record
Abstract
Abstract As the earliest measure of social communication in rodents, ultrasonic vocalizations (USVs) in response to maternal separation are critical in preclinical research on neurodevelopmental disorders (NDDs). While sex differences in both USV production and behavioral outcomes are reported, many studies overlook sex as a biological variable in preclinical NDD models. We aimed to evaluate sex differences in USV call parameters and determine if USVs are differently impacted based on sex in the preclinical maternal immune activation (MIA) model. Results indicate that sex differences in USVs vary with developmental stage and are more pronounced in MIA offspring. Specifically, developmental stage is a moderator of sex differences in USV call duration, with control females emitting longer calls than males in early development (up to postnatal day [PND] 8), but this pattern reverses after PND8. MIA leads to a reduction in call numbers for females compared to same-sex controls in early development, with a reversal post-PND8. MIA decreased call duration and increased total call duration in males, but unlike females, developmental stage did not influence these differences. In males, MIA effects varied by species, with decreased call numbers in rats but increased call numbers in mice. MIA timing (gestational day ≤ 12.5 vs. > 12.5) did not significantly affect results. Our findings highlight the importance of considering sex, developmental timing, and species in USVs research. We discuss how analyzing USV call types and incorporating sex as a biological variable can enhance our understanding of neonatal ultrasonic communication and its translational value in NDD research.
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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 | 0.014 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.024 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".